| Year |
Citation |
Score |
| 2023 |
Koyuncu C, Janowczyk A, Farre X, Pathak T, Mirtti T, Fernandez PL, Pons L, Reder NP, Serafin R, Chow SS, Viswanathan VS, Glaser AK, True LD, Liu JT, Madabhushi A. Visual assessment of 2D levels within 3D pathology datasets of prostate needle biopsies reveals substantial spatial heterogeneity. Laboratory Investigation; a Journal of Technical Methods and Pathology. 100265. PMID 37858679 DOI: 10.1016/j.labinv.2023.100265 |
0.681 |
|
| 2023 |
Li L, Shiradkar R, Gottlieb N, Buzzy C, Hiremath A, Viswanathan VS, MacLennan GT, Lima DO, Gupta K, Shen DL, Tirumani SH, Magi-Galluzzi C, Purysko A, Madabhushi A. Multi-scale statistical deformation based co-registration of prostate MRI and post-surgical whole mount histopathology. Medical Physics. PMID 37742344 DOI: 10.1002/mp.16753 |
0.402 |
|
| 2023 |
Corredor G, Bharadwaj S, Pathak T, Viswanathan VS, Toro P, Madabhushi A. A Review of AI-Based Radiomics and Computational Pathology Approaches in Triple-Negative Breast Cancer: Current Applications and Perspectives. Clinical Breast Cancer. PMID 37380569 DOI: 10.1016/j.clbc.2023.06.004 |
0.321 |
|
| 2023 |
Serafin R, Koyuncu C, Xie W, Huang H, Glaser AK, Reder NP, Janowczyk A, True LD, Madabhushi A, Liu JT. Nondestructive 3D pathology with analysis of nuclear features for prostate cancer risk assessment. The Journal of Pathology. PMID 37232213 DOI: 10.1002/path.6090 |
0.697 |
|
| 2023 |
Chen Y, Li H, Janowczyk A, Toro P, Corredor G, Whitney J, Lu C, Koyuncu CF, Mokhtari M, Buzzy C, Ganesan S, Feldman MD, Fu P, Corbin H, Harbhajanka A, ... ... Madabhushi A, et al. Computational pathology improves risk stratification of a multi-gene assay for early stage ER+ breast cancer. Npj Breast Cancer. 9: 40. PMID 37198173 DOI: 10.1038/s41523-023-00545-y |
0.658 |
|
| 2023 |
Chen Y, Zee J, Janowczyk AR, Rubin J, Toro P, Lafata KJ, Mariani LH, Holzman LB, Hodgin JB, Madabhushi A, Barisoni L. Clinical Relevance of Computationally Derived Attributes of Peritubular Capillaries from Kidney Biopsies. Kidney360. PMID 37016482 DOI: 10.34067/KID.0000000000000116 |
0.646 |
|
| 2022 |
Iyer S, Ismail M, Tamrazi B, Salloum R, de Blank P, Margol A, Correa R, Chen J, Bera K, Statsevych V, Ho ML, Vaidya P, Verma R, Hawes D, Judkins A, ... ... Madabhushi A, et al. Novel MRI deformation-heterogeneity radiomic features are associated with molecular subgroups and overall survival in pediatric medulloblastoma: Preliminary findings from a multi-institutional study. Frontiers in Oncology. 12: 915143. PMID 36620600 DOI: 10.3389/fonc.2022.915143 |
0.51 |
|
| 2022 |
Zhou Y, Koyuncu C, Lu C, Grobholz R, Katz I, Madabhushi A, Janowczyk A. Multi-site cross-organ calibrated deep learning (MuSClD): Automated diagnosis of non-melanoma skin cancer. Medical Image Analysis. 84: 102702. PMID 36516556 DOI: 10.1016/j.media.2022.102702 |
0.647 |
|
| 2022 |
Alilou M, Khorrami M, Prasanna P, Bera K, Gupta A, Viswanathan VS, Patil P, Velu PD, Fu P, Velcheti V, Madabhushi A. A tumor vasculature-based imaging biomarker for predicting response and survival in patients with lung cancer treated with checkpoint inhibitors. Science Advances. 8: eabq4609. PMID 36427313 DOI: 10.1126/sciadv.abq4609 |
0.303 |
|
| 2022 |
Whitney J, Dollinger L, Tamrazi B, Hawes D, Couce M, Marcheque J, Judkins A, Margol A, Madabhushi A. Quantitative Nuclear Histomorphometry Predicts Molecular Subtype and Clinical Outcome in Medulloblastomas: Preliminary Findings. Journal of Pathology Informatics. 13: 100090. PMID 36268104 DOI: 10.1016/j.jpi.2022.100090 |
0.302 |
|
| 2022 |
Chirra P, Sharma A, Bera K, Cohn HM, Kurowski JA, Amann K, Rivero MJ, Madabhushi A, Lu C, Paspulati R, Stein SL, Katz JA, Viswanath SE, Dave M. Integrating Radiomics With Clinicoradiological Scoring Can Predict High-Risk Patients Who Need Surgery in Crohn's Disease: A Pilot Study. Inflammatory Bowel Diseases. PMID 36250776 DOI: 10.1093/ibd/izac211 |
0.632 |
|
| 2022 |
Wang X, Barrera C, Bera K, Viswanathan VS, Azarianpour-Esfahani S, Koyuncu C, Velu P, Feldman MD, Yang M, Fu P, Schalper KA, Mahdi H, Lu C, Velcheti V, Madabhushi A. Spatial interplay patterns of cancer nuclei and tumor-infiltrating lymphocytes (TILs) predict clinical benefit for immune checkpoint inhibitors. Science Advances. 8: eabn3966. PMID 35648850 DOI: 10.1126/sciadv.abn3966 |
0.318 |
|
| 2022 |
Arabyarmohammadi S, Leo P, Viswanathan VS, Janowczyk A, Corredor G, Fu P, Meyerson H, Metheny L, Madabhushi A. Machine Learning to Predict Risk of Relapse Using Cytologic Image Markers in Patients With Acute Myeloid Leukemia Posthematopoietic Cell Transplantation. Jco Clinical Cancer Informatics. 6: e2100156. PMID 35522898 DOI: 10.1200/CCI.21.00156 |
0.653 |
|
| 2022 |
Azarianpour S, Corredor G, Bera K, Leo P, Fu P, Toro P, Joehlin-Price A, Mokhtari M, Mahdi H, Madabhushi A. Computational image features of immune architecture is associated with clinical benefit and survival in gynecological cancers across treatment modalities. Journal For Immunotherapy of Cancer. 10. PMID 35115363 DOI: 10.1136/jitc-2021-003833 |
0.316 |
|
| 2022 |
Ismail M, Prasanna P, Bera K, Statsevych V, Hill V, Singh G, Partovi S, Beig N, McGarry S, Laviolette P, Ahluwalia M, Madabhushi A, Tiwari P. Radiomic Deformation and Textural Heterogeneity (R-DepTH) Descriptor to characterize Tumor Field Effect: Application to Survival Prediction in Glioblastoma. Ieee Transactions On Medical Imaging. PMID 35108202 DOI: 10.1109/TMI.2022.3148780 |
0.516 |
|
| 2021 |
Xie W, Reder NP, Koyuncu CF, Leo P, Hawley S, Huang H, Mao C, Postupna N, Kang S, Serafin R, Gao G, Han Q, Bishop KW, Barner LA, Fu P, ... ... Madabhushi A, et al. Prostate cancer risk stratification via non-destructive 3D pathology with deep learning-assisted gland analysis. Cancer Research. PMID 34853071 DOI: 10.1158/0008-5472.CAN-21-2843 |
0.698 |
|
| 2021 |
Yousif M, van Diest PJ, Laurinavicius A, Rimm D, van der Laak J, Madabhushi A, Schnitt S, Pantanowitz L. Artificial intelligence applied to breast pathology. Virchows Archiv : An International Journal of Pathology. PMID 34791536 DOI: 10.1007/s00428-021-03213-3 |
0.301 |
|
| 2021 |
Miao R, Toth R, Zhou Y, Madabhushi A, Janowczyk A. Quick Annotator: an open-source digital pathology based rapid image annotation tool. The Journal of Pathology. Clinical Research. PMID 34288586 DOI: 10.1002/cjp2.229 |
0.668 |
|
| 2021 |
Hiremath A, Shiradkar R, Fu P, Mahran A, Rastinehad AR, Tewari A, Tirumani SH, Purysko A, Ponsky L, Madabhushi A. An integrated nomogram combining deep learning, Prostate Imaging-Reporting and Data System (PI-RADS) scoring, and clinical variables for identification of clinically significant prostate cancer on biparametric MRI: a retrospective multicentre study. The Lancet. Digital Health. 3: e445-e454. PMID 34167765 DOI: 10.1016/S2589-7500(21)00082-0 |
0.377 |
|
| 2021 |
Peyster EG, Arabyarmohammadi S, Janowczyk A, Azarianpour-Esfahani S, Sekulic M, Cassol C, Blower L, Parwani A, Lal P, Feldman MD, Margulies KB, Madabhushi A. An automated computational image analysis pipeline for histological grading of cardiac allograft rejection. European Heart Journal. PMID 33982079 DOI: 10.1093/eurheartj/ehab241 |
0.637 |
|
| 2021 |
Leo P, Janowczyk A, Elliott R, Janaki N, Bera K, Shiradkar R, Farré X, Fu P, El-Fahmawi A, Shahait M, Kim J, Lee D, Yamoah K, Rebbeck TR, Khani F, ... ... Madabhushi A, et al. Computer extracted gland features from H&E predicts prostate cancer recurrence comparably to a genomic companion diagnostic test: a large multi-site study. Npj Precision Oncology. 5: 35. PMID 33941830 DOI: 10.1038/s41698-021-00174-3 |
0.711 |
|
| 2021 |
Leo P, Chandramouli S, Farré X, Elliott R, Janowczyk A, Bera K, Fu P, Janaki N, El-Fahmawi A, Shahait M, Kim J, Lee D, Yamoah K, Rebbeck TR, Khani F, ... ... Madabhushi A, et al. Computationally Derived Cribriform Area Index from Prostate Cancer Hematoxylin and Eosin Images Is Associated with Biochemical Recurrence Following Radical Prostatectomy and Is Most Prognostic in Gleason Grade Group 2. European Urology Focus. PMID 33941504 DOI: 10.1016/j.euf.2021.04.016 |
0.677 |
|
| 2021 |
Eck B, Chirra PV, Muchhala A, Hall S, Bera K, Tiwari P, Madabhushi A, Seiberlich N, Viswanath SE. Prospective Evaluation of Repeatability and Robustness of Radiomic Descriptors in Healthy Brain Tissue Regions In Vivo Across Systematic Variations in T2-Weighted Magnetic Resonance Imaging Acquisition Parameters. Journal of Magnetic Resonance Imaging : Jmri. PMID 33860966 DOI: 10.1002/jmri.27635 |
0.748 |
|
| 2021 |
Liu JTC, Glaser AK, Bera K, True LD, Reder NP, Eliceiri KW, Madabhushi A. Harnessing non-destructive 3D pathology. Nature Biomedical Engineering. PMID 33589781 DOI: 10.1038/s41551-020-00681-x |
0.307 |
|
| 2020 |
Ismail M, Hill V, Statsevych V, Mason E, Correa R, Prasanna P, Singh G, Bera K, Thawani R, Ahluwalia M, Madabhushi A, Tiwari P. Can Tumor Location on Pre-treatment MRI Predict Likelihood of Pseudo-Progression vs. Tumor Recurrence in Glioblastoma?-A Feasibility Study. Frontiers in Computational Neuroscience. 14: 563439. PMID 33381018 DOI: 10.3389/fncom.2020.563439 |
0.524 |
|
| 2020 |
Lu C, Koyuncu C, Corredor G, Prasanna P, Leo P, Wang X, Janowczyk A, Bera K, Lewis J, Velcheti V, Madabhushi A. Feature-driven local cell graph (FLocK): New computational pathology-based descriptors for prognosis of lung cancer and HPV status of oropharyngeal cancers. Medical Image Analysis. 68: 101903. PMID 33352373 DOI: 10.1016/j.media.2020.101903 |
0.682 |
|
| 2020 |
Verma R, Correa R, Hill VB, Statsevych V, Bera K, Beig N, Mahammedi A, Madabhushi A, Ahluwalia M, Tiwari P. Tumor Habitat-derived Radiomic Features at Pretreatment MRI That Are Prognostic for Progression-free Survival in Glioblastoma Are Associated with Key Morphologic Attributes at Histopathologic Examination: A Feasibility Study. Radiology. Artificial Intelligence. 2: e190168. PMID 33330847 DOI: 10.1148/ryai.2020190168 |
0.562 |
|
| 2020 |
Li L, Shiradkar R, Leo P, Algohary A, Fu P, Tirumani SH, Mahran A, Buzzy C, Obmann VC, Mansoori B, El-Fahmawi A, Shahait M, Tewari A, Magi-Galluzzi C, Lee D, ... ... Madabhushi A, et al. A novel imaging based Nomogram for predicting post-surgical biochemical recurrence and adverse pathology of prostate cancer from pre-operative bi-parametric MRI. Ebiomedicine. 63: 103163. PMID 33321450 DOI: 10.1016/j.ebiom.2020.103163 |
0.328 |
|
| 2020 |
Chen Y, Zee J, Smith A, Jayapandian C, Hodgin J, Howell D, Palmer M, Thomas D, Cassol C, Farris AB, Perkinson K, Madabhushi A, Barisoni L, Janowczyk A. Assessment of a computerized quantitative quality control tool for kidney whole slide image biopsies. The Journal of Pathology. PMID 33197281 DOI: 10.1002/path.5590 |
0.685 |
|
| 2020 |
Sadri AR, Janowczyk A, Zhou R, Verma R, Beig N, Antunes J, Madabhushi A, Tiwari P, Viswanath SE. Technical Note: MRQy - An Open-Source Tool for Quality Control of MR Imaging Data. Medical Physics. PMID 33176026 DOI: 10.1002/mp.14593 |
0.823 |
|
| 2020 |
Bera K, Katz I, Madabhushi A. Reimagining T Staging Through Artificial Intelligence and Machine Learning Image Processing Approaches in Digital Pathology. Jco Clinical Cancer Informatics. 4: 1039-1050. PMID 33166198 DOI: 10.1200/CCI.20.00110 |
0.331 |
|
| 2020 |
Lu C, Bera K, Wang X, Prasanna P, Xu J, Janowczyk A, Beig N, Yang M, Fu P, Lewis J, Choi H, Schmid RA, Berezowska S, Schalper K, Rimm D, ... ... Madabhushi A, et al. A prognostic model for overall survival of patients with early-stage non-small cell lung cancer: a multicentre, retrospective study. The Lancet. Digital Health. 2: e594-e606. PMID 33163952 DOI: 10.1016/s2589-7500(20)30225-9 |
0.664 |
|
| 2020 |
Beig N, Singh S, Bera K, Prasanna P, Singh G, Chen J, SaeedBamashmos A, Barnett A, Hunter K, Statsevych V, Hill VB, Varadan V, Madabhushi A, Ahluwalia MS, Tiwari P. Sexually dimorphic radiogenomic models identify distinct imaging and biological pathways that are prognostic of overall survival in Glioblastoma. Neuro-Oncology. PMID 33068415 DOI: 10.1093/neuonc/noaa231 |
0.502 |
|
| 2020 |
Chandramouli S, Leo P, Lee G, Elliott R, Davis C, Zhu G, Fu P, Epstein JI, Veltri R, Madabhushi A. Computer Extracted Features from Initial H&E Tissue Biopsies Predict Disease Progression for Prostate Cancer Patients on Active Surveillance. Cancers. 12. PMID 32967377 DOI: 10.3390/Cancers12092708 |
0.456 |
|
| 2020 |
Shiradkar R, Panda A, Leo P, Janowczyk A, Farre X, Janaki N, Li L, Pahwa S, Mahran A, Buzzy C, Fu P, Elliott R, MacLennan G, Ponsky L, Gulani V, ... Madabhushi A, et al. Correction to: T1 and T2 MR fingerprinting measurements of prostate cancer and prostatitis correlate with deep learning-derived estimates of epithelium, lumen, and stromal composition on corresponding whole mount histopathology. European Radiology. PMID 32945970 DOI: 10.1007/s00330-020-07285-8 |
0.658 |
|
| 2020 |
Shiradkar R, Panda A, Leo P, Janowczyk A, Farre X, Janaki N, Li L, Pahwa S, Mahran A, Buzzy C, Fu P, Elliott R, MacLennan G, Ponsky L, Gulani V, ... Madabhushi A, et al. T1 and T2 MR fingerprinting measurements of prostate cancer and prostatitis correlate with deep learning-derived estimates of epithelium, lumen, and stromal composition on corresponding whole mount histopathology. European Radiology. PMID 32876839 DOI: 10.1007/S00330-020-07214-9 |
0.69 |
|
| 2020 |
Barisoni L, Lafata KJ, Hewitt SM, Madabhushi A, Balis UGJ. Digital pathology and computational image analysis in nephropathology. Nature Reviews. Nephrology. PMID 32848206 DOI: 10.1038/S41581-020-0321-6 |
0.417 |
|
| 2020 |
Jayapandian CP, Chen Y, Janowczyk AR, Palmer MB, Cassol CA, Sekulic M, Hodgin JB, Zee J, Hewitt SM, O'Toole J, Toro P, Sedor JR, Barisoni L, Madabhushi A. Development and evaluation of deep learning-based segmentation of histologic structures in the kidney cortex with multiple histologic stains. Kidney International. PMID 32835732 DOI: 10.1016/J.Kint.2020.07.044 |
0.685 |
|
| 2020 |
Moosavi A, Figueiredo N, Prasanna P, K Srivastava S, Sharma S, Madabhushi A, Ehlers J. Imaging Features of Vessels and Leakage Patterns Predict Extended Interval Aflibercept Dosing Using Ultra-Widefield Angiography in Retinal Vascular Disease: Findings from the PERMEATE Study. Ieee Transactions On Bio-Medical Engineering. PMID 32822291 DOI: 10.1109/Tbme.2020.3018464 |
0.352 |
|
| 2020 |
Prasanna P, Bobba V, Figueiredo N, Sevgi DD, Lu C, Braman N, Alilou M, Sharma S, Srivastava SK, Madabhushi A, Ehlers JP. Radiomics-based assessment of ultra-widefield leakage patterns and vessel network architecture in the PERMEATE study: insights into treatment durability. The British Journal of Ophthalmology. PMID 32816791 DOI: 10.1136/Bjophthalmol-2020-317182 |
0.325 |
|
| 2020 |
Algohary A, Shiradkar R, Pahwa S, Purysko A, Verma S, Moses D, Shnier R, Haynes AM, Delprado W, Thompson J, Tirumani S, Mahran A, Rastinehad AR, Ponsky L, Stricker PD, ... Madabhushi A, et al. Combination of Peri-Tumoral and Intra-Tumoral Radiomic Features on Bi-Parametric MRI Accurately Stratifies Prostate Cancer Risk: A Multi-Site Study. Cancers. 12. PMID 32781640 DOI: 10.3390/Cancers12082200 |
0.422 |
|
| 2020 |
Alvarez-Jimenez C, Antunes JT, Talasila N, Bera K, Brady JT, Gollamudi J, Marderstein E, Kalady MF, Purysko A, Willis JE, Stein S, Friedman K, Paspulati R, Delaney CP, Romero E, ... Madabhushi A, et al. Radiomic Texture and Shape Descriptors of the Rectal Environment on Post-Chemoradiation T2-Weighted MRI are Associated with Pathologic Tumor Stage Regression in Rectal Cancers: A Retrospective, Multi-Institution Study. Cancers. 12. PMID 32722082 DOI: 10.3390/Cancers12082027 |
0.719 |
|
| 2020 |
Hiremath A, Shiradkar R, Merisaari H, Prasanna P, Ettala O, Taimen P, Aronen HJ, Boström PJ, Jambor I, Madabhushi A. Test-retest repeatability of a deep learning architecture in detecting and segmenting clinically significant prostate cancer on apparent diffusion coefficient (ADC) maps. European Radiology. PMID 32700021 DOI: 10.1007/S00330-020-07065-4 |
0.414 |
|
| 2020 |
Yan C, Nakane K, Wang X, Fu Y, Lu H, Fan X, Feldman MD, Madabhushi A, Xu J. Automated gleason grading on prostate biopsy slides by statistical representations of homology profile. Computer Methods and Programs in Biomedicine. 194: 105528. PMID 32470903 DOI: 10.1016/J.Cmpb.2020.105528 |
0.399 |
|
| 2020 |
Antunes JT, Ofshteyn A, Bera K, Wang EY, Brady JT, Willis JE, Friedman KA, Marderstein EL, Kalady MF, Stein SL, Purysko AS, Paspulati R, Gollamudi J, Madabhushi A, Viswanath SE. Radiomic Features of Primary Rectal Cancers on Baseline T -Weighted MRI Are Associated With Pathologic Complete Response to Neoadjuvant Chemoradiation: A Multisite Study. Journal of Magnetic Resonance Imaging : Jmri. PMID 32216127 DOI: 10.1002/Jmri.27140 |
0.715 |
|
| 2020 |
Chen Y, Janowczyk A, Madabhushi A. Quantitative Assessment of the Effects of Compression on Deep Learning in Digital Pathology Image Analysis. Jco Clinical Cancer Informatics. 4: 221-233. PMID 32155093 DOI: 10.1200/CCI.19.00068 |
0.697 |
|
| 2020 |
Bhargava HK, Leo P, Elliott R, Janowczyk A, Whitney J, Gupta S, Fu P, Yamoah K, Khani F, Robinson BD, Rebbeck TR, Feldman M, Lal P, Madabhushi A. Computationally Derived Image Signature of Stromal Morphology Is Prognostic of Prostate Cancer Recurrence Following Prostatectomy in African American Patients. Clinical Cancer Research : An Official Journal of the American Association For Cancer Research. PMID 32139401 DOI: 10.1158/1078-0432.Ccr-19-2659 |
0.715 |
|
| 2020 |
Khorrami M, Bera K, Leo P, Vaidya P, Patil P, Thawani R, Velu P, Rajiah P, Alilou M, Choi H, Feldman MD, Gilkeson RC, Linden P, Fu P, Pass H, ... ... Madabhushi A, et al. Stable and discriminating radiomic predictor of recurrence in early stage non-small cell lung cancer: Multi-site study. Lung Cancer (Amsterdam, Netherlands). 142: 90-97. PMID 32120229 DOI: 10.1016/J.Lungcan.2020.02.018 |
0.319 |
|
| 2020 |
Beig N, Bera K, Prasanna P, Antunes J, Correa R, Singh S, Saeed Bamashmos A, Ismail M, Braman N, Verma R, Hill VB, Statsevych V, Ahluwalia MS, Varadan V, Madabhushi A, et al. Radiogenomic-based survival risk stratification of tumor habitat on Gd-T1w MRI is associated with biological processes in Glioblastoma. Clinical Cancer Research : An Official Journal of the American Association For Cancer Research. PMID 32079590 DOI: 10.1158/1078-0432.Ccr-19-2556 |
0.57 |
|
| 2020 |
Madabhushi A, Feldman MD, Leo P. Deep-learning approaches for Gleason grading of prostate biopsies. The Lancet. Oncology. PMID 31926804 DOI: 10.1016/S1470-2045(19)30793-4 |
0.339 |
|
| 2020 |
Kunte S, Braman N, Bera K, Leo P, Abraham J, Montero AJ, Madabhushi A. Radiomics risk score (RRS) on CT to predict survival and response to CDK 4/6 inhibitors in hormone receptor (HR) positive metastatic breast cancer (MBC). Journal of Clinical Oncology. 38: e13041-e13041. DOI: 10.1200/Jco.2020.38.15_Suppl.E13041 |
0.373 |
|
| 2020 |
Koyuncu C, Corredor G, Lu C, Toro P, Bera K, Fu P, Koyfman SA, Chute D, Adelstein DJ, Thorstad W, Bishop JA, Faraji F, Lewis JS, Madabhushi A. Combination of tumor multinucleation and spatial arrangement of tumor-infiltrating lymphocytes to predict overall survival in oropharyngeal squamous cell carcinoma: A multisite study. Journal of Clinical Oncology. 38: 6566-6566. DOI: 10.1200/Jco.2020.38.15_Suppl.6566 |
0.349 |
|
| 2020 |
Corredor G, Lu C, Koyuncu C, Bera K, Toro P, Fu P, Koyfman SA, Chute D, Adelstein DJ, Thorstad W, Bishop JA, Faraji F, Lewis J, Madabhushi A. Computerized features of spatial interplay of tumor-infiltrating lymphocytes predict disease recurrence in p16+ oropharyngeal squamous cell carcinoma: A multisite validation study. Journal of Clinical Oncology. 38: 6559-6559. DOI: 10.1200/Jco.2020.38.15_Suppl.6559 |
0.355 |
|
| 2020 |
Azarianpour Esfahani S, Corredor G, Bera K, Fu P, Joehlin-Price A, Mahdi H, Madabhushi A. Computerized features of spatial arrangement of tumor-infiltrating lymphocytes from H&E images predicts survival and response to checkpoint inhibitors in gynecologic cancers. Journal of Clinical Oncology. 38: 6074-6074. DOI: 10.1200/Jco.2020.38.15_Suppl.6074 |
0.394 |
|
| 2020 |
Maidment T, Braman N, Chen Y, Mehrkhani F, Yankevich U, Plecha D, Madabhushi A. Abstract PD9-03: A combination of intra- and peri-lesional deep learning classifiers from multiple views enables accurate diagnosis of architectural distortion malignancy with digital breast tomosynthesis Cancer Research. 80. DOI: 10.1158/1538-7445.Sabcs19-Pd9-03 |
0.367 |
|
| 2020 |
Li H, Bera K, Gilmore H, Davidson NE, Goldstein LJ, Madabhushi A. Abstract P5-06-16: Histomorphometric measure of disorder of collagen fiber orientation is associated with risk of recurrence in ER+ breast cancers in ECOG-ACRIN E2197 and TCGA-BRCA Cancer Research. 80. DOI: 10.1158/1538-7445.Sabcs19-P5-06-16 |
0.31 |
|
| 2020 |
Li H, Bera K, Gilmore H, Zhang Z, Cuzick J, Thorat MA, Madabhushi A. Abstract P5-06-15: Computer extracted features of nuclear shape, orientation disorder and texture from H&E Whole slide images are associated with disease-free survival in ductal carcinoma in situ (DCIS) Cancer Research. 80. DOI: 10.1158/1538-7445.Sabcs19-P5-06-15 |
0.427 |
|
| 2020 |
Braman N, Adoui ME, Vulchi M, Turk P, Etesami M, Fu P, Drisis S, Varadan V, Plecha D, Benjelloun M, Abraham J, Madabhushi A. Abstract P4-10-13: Validation of neural network approach for the prediction of HER2-targeted neoadjuvant chemotherapy response from pretreatment MRI: A multi-site study Cancer Research. 80. DOI: 10.1158/1538-7445.Sabcs19-P4-10-13 |
0.406 |
|
| 2020 |
Braman N, Prasanna P, Bera K, Alilou M, Vulchi M, Etesami M, Turk P, Abraham J, Plecha D, Madabhushi A. Abstract P1-10-06: Radiomic measurements of tumor-associated vasculature morphology and function on pretreatment dynamic MRI identifies responders to neoadjuvant chemotherapy Cancer Research. 80. DOI: 10.1158/1538-7445.Sabcs19-P1-10-06 |
0.419 |
|
| 2020 |
Shiradkar* R, Mahran A, Sharma S, Conroy B, Tirumani SH, Ponsky L, Madabhushi A. MP81-06 RADIOMIC FEATURES OF PROSTATE CANCER PATIENTS (GLEASON GRADE GROUP = 2) SHOW DIFFERENCES BETWEEN AFRICAN AMERICAN AND CAUCASIAN POPULATIONS ON BI-PARAMETRIC MRI The Journal of Urology. 203: e1238. DOI: 10.1097/Ju.0000000000000973.06 |
0.403 |
|
| 2020 |
Hiremath* A, Shiradkar R, Merisaari H, Li L, Prasanna P, Ettala O, Taimen P, Aronen H, Boström P, Pierce J, Tirumani SH, Rastinehad A, Jambor I, Purysko A, Madabhushi A. PD57-05 A DEEP LEARNING NETWORK ALONG WITH PIRADS CAN DISTINGUISH CLINICALLY SIGNIFICANT AND INSIGNIFICANT PROSTATE CANCER ON BI-PARAMETRIC MRI The Journal of Urology. 203: e1195. DOI: 10.1097/Ju.0000000000000967.05 |
0.352 |
|
| 2020 |
Leo* P, Elliott R, Janowczyk A, Janaki N, Bera K, Shiradkar R, El-Fahmawi A, Kim J, Shahait M, Shah A, Thulasidass H, Tewari A, Gupta S, Shih N, Feldman M, ... ... Madabhushi A, et al. PD52-02 COMPUTER-EXTRACTED FEATURES OF GLAND MORPHOLOGY FROM DIGITAL TISSUE IMAGES IS COMPARABLE TO DECIPHER FOR PROGNOSIS OF BIOCHEMICAL RECURRENCE RISK POST-SURGERY The Journal of Urology. 203: e1089-e1090. DOI: 10.1097/Ju.0000000000000954.02 |
0.685 |
|
| 2020 |
Willis J, Lu C, Butler K, Kumar N, Madabhushi A. Mo1071 CANCER NUCLEAR FEATURES EXTRACTED FROM PATHOLOGY IMAGES IDENTIFY STAGE 2 COLON CANCERS THAT RECUR Gastroenterology. 158: S-778-S-779. DOI: 10.1016/S0016-5085(20)32617-2 |
0.429 |
|
| 2019 |
Khorrami M, Prasanna P, Gupta A, Patil P, Velu PD, Thawani R, Corredor G, Alilou M, Bera K, Fu P, Feldman M, Velcheti V, Madabhushi A. Changes in CT radiomic features associated with lymphocyte distribution predict overall survival and response to immunotherapy in non-small cell lung cancer. Cancer Immunology Research. PMID 31719058 DOI: 10.1158/2326-6066.Cir-19-0476 |
0.368 |
|
| 2019 |
Merisaari H, Taimen P, Shiradkar R, Ettala O, Pesola M, Saunavaara J, Boström PJ, Madabhushi A, Aronen HJ, Jambor I. Repeatability of radiomics and machine learning for DWI: Short-term repeatability study of 112 patients with prostate cancer. Magnetic Resonance in Medicine. PMID 31703155 DOI: 10.1002/Mrm.28058 |
0.369 |
|
| 2019 |
Alilou M, Orooji M, Beig N, Prasanna P, Rajiah P, Donatelli C, Velcheti V, Rakshit S, Yang M, Jacono F, Gilkeson R, Linden P, Madabhushi A. Author Correction: Quantitative vessel tortuosity: A potential CT imaging biomarker for distinguishing lung granulomas from adenocarcinomas. Scientific Reports. 9: 15873. PMID 31659229 DOI: 10.1038/S41598-019-52008-9 |
0.322 |
|
| 2019 |
Li H, Whitney J, Bera K, Gilmore H, Thorat MA, Badve S, Madabhushi A. Quantitative nuclear histomorphometric features are predictive of Oncotype DX risk categories in ductal carcinoma in situ: preliminary findings. Breast Cancer Research : Bcr. 21: 114. PMID 31623652 DOI: 10.1186/S13058-019-1200-6 |
0.341 |
|
| 2019 |
Khorrami M, Jain P, Bera K, Alilou M, Thawani R, Patil P, Ahmad U, Murthy S, Stephans K, Fu P, Velcheti V, Madabhushi A. Corrigendum to "Predicting pathologic response to neoadjuvant chemoradiation in resectable stage III non-small cell lung cancer patients using computed tomography radiomic features" [Lung Cancer 135 (September) (2019) 1-9]. Lung Cancer (Amsterdam, Netherlands). 136: 156. PMID 31564290 DOI: 10.1016/J.Lungcan.2019.08.012 |
0.308 |
|
| 2019 |
Khorrami M, Jain P, Bera K, Alilou M, Thawani R, Patil P, Ahmad U, Murthy S, Stephans K, Fu P, Velcheti V, Madabhushi A. Predicting pathologic response to neoadjuvant chemoradiation in resectable stage III non-small cell lung cancer patients using computed tomography radiomic features. Lung Cancer (Amsterdam, Netherlands). 135: 1-9. PMID 31446979 DOI: 10.1016/J.Lungcan.2019.06.020 |
0.331 |
|
| 2019 |
Bera K, Schalper KA, Rimm DL, Velcheti V, Madabhushi A. Artificial intelligence in digital pathology - new tools for diagnosis and precision oncology. Nature Reviews. Clinical Oncology. PMID 31399699 DOI: 10.1038/S41571-019-0252-Y |
0.4 |
|
| 2019 |
Chirra P, Leo P, Yim M, Bloch BN, Rastinehad AR, Purysko A, Rosen M, Madabhushi A, Viswanath SE. Multisite evaluation of radiomic feature reproducibility and discriminability for identifying peripheral zone prostate tumors on MRI. Journal of Medical Imaging (Bellingham, Wash.). 6: 024502. PMID 31259199 DOI: 10.1117/1.Jmi.6.2.024502 |
0.732 |
|
| 2019 |
Prasanna P, Karnawat A, Ismail M, Madabhushi A, Tiwari P. Radiomics-based convolutional neural network for brain tumor segmentation on multiparametric magnetic resonance imaging. Journal of Medical Imaging (Bellingham, Wash.). 6: 024005. PMID 31093517 DOI: 10.1117/1.Jmi.6.2.024005 |
0.638 |
|
| 2019 |
Janowczyk A, Zuo R, Gilmore H, Feldman M, Madabhushi A. HistoQC: An Open-Source Quality Control Tool for Digital Pathology Slides. Jco Clinical Cancer Informatics. 1-7. PMID 30990737 DOI: 10.1200/CCI.18.00157 |
0.636 |
|
| 2019 |
Purysko AS, Magi-Galluzzi C, Mian OY, Sittenfeld S, Davicioni E, du Plessis M, Buerki C, Bullen J, Li L, Madabhushi A, Stephenson A, Klein EA. Correlation between MRI phenotypes and a genomic classifier of prostate cancer: preliminary findings. European Radiology. PMID 30847589 DOI: 10.1007/S00330-019-06114-X |
0.4 |
|
| 2019 |
Xu J, Gong L, Wang G, Lu C, Gilmore H, Zhang S, Madabhushi A. Convolutional neural network initialized active contour model with adaptive ellipse fitting for nuclear segmentation on breast histopathological images. Journal of Medical Imaging (Bellingham, Wash.). 6: 017501. PMID 30840729 DOI: 10.1117/1.Jmi.6.1.017501 |
0.429 |
|
| 2019 |
Viswanath SE, Chirra PV, Yim MC, Rofsky NM, Purysko AS, Rosen MA, Bloch BN, Madabhushi A. Comparing radiomic classifiers and classifier ensembles for detection of peripheral zone prostate tumors on T2-weighted MRI: a multi-site study. Bmc Medical Imaging. 19: 22. PMID 30819131 DOI: 10.1186/S12880-019-0308-6 |
0.752 |
|
| 2019 |
Prasanna P, Rogers L, Lam TC, Cohen M, Siddalingappa A, Wolansky L, Pinho M, Gupta A, Hatanpaa KJ, Madabhushi A, Tiwari P. Disorder in Pixel-Level Edge Directions on T1WI Is Associated with the Degree of Radiation Necrosis in Primary and Metastatic Brain Tumors: Preliminary Findings. Ajnr. American Journal of Neuroradiology. PMID 30733252 DOI: 10.3174/Ajnr.A5958 |
0.543 |
|
| 2019 |
Prasanna P, Mitra J, Beig N, Nayate A, Patel J, Ghose S, Thawani R, Partovi S, Madabhushi A, Tiwari P. Mass Effect Deformation Heterogeneity (MEDH) on Gadolinium-contrast T1-weighted MRI is associated with decreased survival in patients with right cerebral hemisphere Glioblastoma: A feasibility study. Scientific Reports. 9: 1145. PMID 30718547 DOI: 10.1038/S41598-018-37615-2 |
0.535 |
|
| 2019 |
Bui MM, Riben MW, Allison KH, Chlipala E, Colasacco C, Kahn AG, Lacchetti C, Madabhushi A, Pantanowitz L, Salama ME, Stewart RL, Thomas NE, Tomaszewski JE, Hammond ME. Quantitative Image Analysis of Human Epidermal Growth Factor Receptor 2 Immunohistochemistry for Breast Cancer: Guideline From the College of American Pathologists. Archives of Pathology & Laboratory Medicine. PMID 30645156 DOI: 10.5858/Arpa.2018-0378-Cp |
0.418 |
|
| 2019 |
Madabhushi A. Digital pathology image analysis: opportunities and challenges. Imaging in Medicine. 1: 7-10. PMID 30147749 DOI: 10.2217/Iim.09.9 |
0.409 |
|
| 2019 |
Li L, Shiradkar R, Leo P, Purysko A, Algohary A, Klein EA, Magi-Galluzzi C, Madabhushi A. Association of radiomic features from prostate bi-parametric MRI with Decipher risk categories to predict risk for biochemical recurrence post-prostatectomy. Journal of Clinical Oncology. 37: e16561-e16561. DOI: 10.1200/Jco.2019.37.15_Suppl.E16561 |
0.396 |
|
| 2019 |
Vulchi M, El Adoui M, Braman N, Turk P, Etesami M, Drisis S, Plecha D, Benjelloun M, Madabhushi A, Abraham J. Development and external validation of a deep learning model for predicting response to HER2-targeted neoadjuvant therapy from pretreatment breast MRI. Journal of Clinical Oncology. 37: 593-593. DOI: 10.1200/Jco.2019.37.15_Suppl.593 |
0.402 |
|
| 2019 |
Leo P, Janowczyk A, Elliott R, Janaki N, Shiradkar R, Farrè X, Yamoah K, Rebbeck T, Shih N, Khani F, Robinson BD, Eklund L, Ettala O, Taimen P, Bostrom P, ... ... Madabhushi A, et al. Computerized histomorphometric features of glandular architecture predict risk of biochemical recurrence following radical prostatectomy: A multisite study. Journal of Clinical Oncology. 37: 5060-5060. DOI: 10.1200/Jco.2019.37.15_Suppl.5060 |
0.716 |
|
| 2019 |
Prasanna P, Khorrami M, Gupta A, Patil PD, Khunger M, Velu P, Bera K, Alilou M, Velcheti V, Madabhushi A. Intra and perinodular CT delta radiomic features associated with early response to predict overall survival (OS) in immunotherapy-treated non-small cell lung cancer (NSCLC): A multisite multi-agent study. Journal of Clinical Oncology. 37: 2588-2588. DOI: 10.1200/Jco.2019.37.15_Suppl.2588 |
0.356 |
|
| 2019 |
Purysko* A, Magi-Galluzzi C, Mian O, Davicioni E, Plessis Md, Buerki C, Bullen J, Li L, Madabhushi A, Stephenson A, Klein E. MP28-04 CORRELATION BETWEEN MRI PHENOTYPES AND A GENOMIC CLASSIFIER OF PROSTATE CANCER Journal of Urology. 201. DOI: 10.1097/01.Ju.0000555709.00017.09 |
0.436 |
|
| 2019 |
Ismail M, Correa R, Bera K, Saeed Bamashmos A, Statsevych V, Prasanna P, Beig N, Madabhushi A, Ahluwalia M, Tiwari P. NIMG-75. RADIOMIC FEATURES LOCALIZED TO STEREOTACTIC BIOPSY LOCATIONS CAN CAPTURE EGFR PRESENCE IN GLIOBLASTOMA Neuro-Oncology. 21: vi178-vi178. DOI: 10.1093/Neuonc/Noz175.744 |
0.597 |
|
| 2019 |
Beig N, Ismail M, Saeed Bamashmos A, Statsevych V, Hill V, Madabhushi A, Ahluwalia M, Tiwari P. EPID-33. GENDER-SPECIFIC PROBABILISTIC ATLASES OF GLIOBLASTOMA REVEAL IMPACT OF TUMOR LOCATION ON PROGRESSION FREE SURVIVAL Neuro-Oncology. 21: vi81-vi82. DOI: 10.1093/Neuonc/Noz175.333 |
0.535 |
|
| 2019 |
Alilou M, Patil P, Fu P, Bera K, Velcheti V, Madabhushi A, Vaidya P. P1.04-25 CT Based Vessel Tortuosity Features Are Prognostic of Overall Survival and Predictive of Immunotherapy Response in NSCLC Patients Journal of Thoracic Oncology. 14: S449. DOI: 10.1016/J.Jtho.2019.08.928 |
0.301 |
|
| 2019 |
Vaidya P, Bera K, Wang X, Patil P, Velcheti V, Madabhushi A. P2.17-35 Integrating CT Radiomic & Quantitative Histomorphometric Whole Slide Image Features Predicts Disease Free Survival in ES-NSCLC Journal of Thoracic Oncology. 14: S898. DOI: 10.1016/J.Jtho.2019.08.1946 |
0.378 |
|
| 2018 |
Hipp JD, Johann DJ, Chen Y, Madabhushi A, Monaco J, Cheng J, Rodriguez-Canales J, Stumpe MC, Riedlinger G, Rosenberg AZ, Hanson JC, Kunju LP, Emmert-Buck MR, Balis UJ, Tangrea MA. Computer-Aided Laser Dissection: A Microdissection Workflow Leveraging Image Analysis Tools. Journal of Pathology Informatics. 9: 45. PMID 30622835 DOI: 10.4103/Jpi.Jpi_60_18 |
0.315 |
|
| 2018 |
Beig N, Khorrami M, Alilou M, Prasanna P, Braman N, Orooji M, Rakshit S, Bera K, Rajiah P, Ginsberg J, Donatelli C, Thawani R, Yang M, Jacono F, Tiwari P, ... ... Madabhushi A, et al. Perinodular and Intranodular Radiomic Features on Lung CT Images Distinguish Adenocarcinomas from Granulomas. Radiology. 180910. PMID 30561278 DOI: 10.1148/Radiol.2018180910 |
0.616 |
|
| 2018 |
Ismail M, Hill V, Statsevych V, Huang R, Prasanna P, Correa R, Singh G, Bera K, Beig N, Thawani R, Madabhushi A, Aahluwalia M, Tiwari P. Shape Features of the Lesion Habitat to Differentiate Brain Tumor Progression from Pseudoprogression on Routine Multiparametric MRI: A Multisite Study. Ajnr. American Journal of Neuroradiology. PMID 30385468 DOI: 10.3174/Ajnr.A5858 |
0.588 |
|
| 2018 |
Alilou M, Orooji M, Beig N, Prasanna P, Rajiah P, Donatelli C, Velcheti V, Rakshit S, Yang M, Jacono F, Gilkeson R, Linden P, Madabhushi A. Quantitative vessel tortuosity: A potential CT imaging biomarker for distinguishing lung granulomas from adenocarcinomas. Scientific Reports. 8: 15290. PMID 30327507 DOI: 10.1038/S41598-018-33473-0 |
0.375 |
|
| 2018 |
Leo P, Elliott R, Shih NNC, Gupta S, Feldman M, Madabhushi A. Stable and discriminating features are predictive of cancer presence and Gleason grade in radical prostatectomy specimens: a multi-site study. Scientific Reports. 8: 14918. PMID 30297720 DOI: 10.1038/S41598-018-33026-5 |
0.452 |
|
| 2018 |
Corredor G, Wang X, Zhou Y, Lu C, Fu P, Syrigos KN, Rimm DL, Yang M, Romero E, Schalper KA, Velcheti V, Madabhushi A. Spatial architecture and arrangement of tumor-infiltrating lymphocytes for predicting likelihood of recurrence in early-stage non-small cell lung cancer. Clinical Cancer Research : An Official Journal of the American Association For Cancer Research. PMID 30201760 DOI: 10.1158/1078-0432.Ccr-18-2013 |
0.356 |
|
| 2018 |
Penzias G, Singanamalli A, Elliott R, Gollamudi J, Shih N, Feldman M, Stricker PD, Delprado W, Tiwari S, Böhm M, Haynes AM, Ponsky L, Fu P, Tiwari P, Viswanath S, ... Madabhushi A, et al. Identifying the morphologic basis for radiomic features in distinguishing different Gleason grades of prostate cancer on MRI: Preliminary findings. Plos One. 13: e0200730. PMID 30169514 DOI: 10.1371/Journal.Pone.0200730 |
0.8 |
|
| 2018 |
Lu C, Romo-Bucheli D, Wang X, Janowczyk A, Ganesan S, Gilmore H, Rimm D, Madabhushi A. Nuclear shape and orientation features from H&E images predict survival in early-stage estrogen receptor-positive breast cancers. Laboratory Investigation; a Journal of Technical Methods and Pathology. PMID 29959421 DOI: 10.1038/S41374-018-0095-7 |
0.721 |
|
| 2018 |
Carleton NM, Lee G, Madabhushi A, Veltri RW. Advances in the computational and molecular understanding of the prostate cancer cell nucleus. Journal of Cellular Biochemistry. PMID 29923622 DOI: 10.1002/Jcb.27156 |
0.417 |
|
| 2018 |
Whitney J, Corredor G, Janowczyk A, Ganesan S, Doyle S, Tomaszewski J, Feldman M, Gilmore H, Madabhushi A. Quantitative nuclear histomorphometry predicts oncotype DX risk categories for early stage ER+ breast cancer. Bmc Cancer. 18: 610. PMID 29848291 DOI: 10.1186/S12885-018-4448-9 |
0.736 |
|
| 2018 |
Cruz-Roa A, Gilmore H, Basavanhally A, Feldman M, Ganesan S, Shih N, Tomaszewski J, Madabhushi A, González F. High-throughput adaptive sampling for whole-slide histopathology image analysis (HASHI) via convolutional neural networks: Application to invasive breast cancer detection. Plos One. 13: e0196828. PMID 29795581 DOI: 10.1371/Journal.Pone.0196828 |
0.774 |
|
| 2018 |
Shiradkar R, Ghose S, Jambor I, Taimen P, Ettala O, Purysko AS, Madabhushi A. Radiomic features from pretreatment biparametric MRI predict prostate cancer biochemical recurrence: Preliminary findings. Journal of Magnetic Resonance Imaging : Jmri. PMID 29734484 DOI: 10.1002/Jmri.26178 |
0.453 |
|
| 2018 |
Janowczyk A, Doyle S, Gilmore H, Madabhushi A. A resolution adaptive deep hierarchical (RADHicaL) learning scheme applied to nuclear segmentation of digital pathology images. Computer Methods in Biomechanics and Biomedical Engineering. Imaging & Visualization. 6: 270-276. PMID 29732269 DOI: 10.1080/21681163.2016.1141063 |
0.793 |
|
| 2018 |
Orooji M, Alilou M, Rakshit S, Beig N, Khorrami MH, Rajiah P, Thawani R, Ginsberg J, Donatelli C, Yang M, Jacono F, Gilkeson R, Velcheti V, Linden P, Madabhushi A. Combination of computer extracted shape and texture features enables discrimination of granulomas from adenocarcinoma on chest computed tomography. Journal of Medical Imaging (Bellingham, Wash.). 5: 024501. PMID 29721515 DOI: 10.1117/1.Jmi.5.2.024501 |
0.36 |
|
| 2018 |
Nirschl JJ, Janowczyk A, Peyster EG, Frank R, Margulies KB, Feldman MD, Madabhushi A. A deep-learning classifier identifies patients with clinical heart failure using whole-slide images of H&E tissue. Plos One. 13: e0192726. PMID 29614076 DOI: 10.1371/Journal.Pone.0192726 |
0.798 |
|
| 2018 |
Peyster EG, Madabhushi A, Margulies KB. Advanced Morphologic Analysis for Diagnosing Allograft Rejection: The Case of Cardiac Transplant Rejection. Transplantation. PMID 29570167 DOI: 10.1097/Tp.0000000000002189 |
0.36 |
|
| 2018 |
Algohary A, Viswanath S, Shiradkar R, Ghose S, Pahwa S, Moses D, Jambor I, Shnier R, Böhm M, Haynes AM, Brenner P, Delprado W, Thompson J, Pulbrock M, Purysko AS, ... ... Madabhushi A, et al. Radiomic features on MRI enable risk categorization of prostate cancer patients on active surveillance: Preliminary findings. Journal of Magnetic Resonance Imaging : Jmri. PMID 29469937 DOI: 10.1002/Jmri.25983 |
0.741 |
|
| 2018 |
Antunes J, Viswanath S, Brady JT, Crawshaw B, Ros P, Steele S, Delaney CP, Paspulati R, Willis J, Madabhushi A. Coregistration of Preoperative MRI with Ex Vivo Mesorectal Pathology Specimens to Spatially Map Post-treatment Changes in Rectal Cancer Onto In Vivo Imaging: Preliminary Findings. Academic Radiology. PMID 29371120 DOI: 10.1016/J.Acra.2017.12.006 |
0.717 |
|
| 2018 |
Beig N, Patel J, Prasanna P, Hill V, Gupta A, Correa R, Bera K, Singh S, Partovi S, Varadan V, Ahluwalia M, Madabhushi A, Tiwari P. Radiogenomic analysis of hypoxia pathway is predictive of overall survival in Glioblastoma. Scientific Reports. 8: 7. PMID 29311558 DOI: 10.1038/S41598-017-18310-0 |
0.608 |
|
| 2018 |
Thawani R, McLane M, Beig N, Ghose S, Prasanna P, Velcheti V, Madabhushi A. Radiomics and radiogenomics in lung cancer: A review for the clinician. Lung Cancer (Amsterdam, Netherlands). 115: 34-41. PMID 29290259 DOI: 10.1016/J.Lungcan.2017.10.015 |
0.415 |
|
| 2018 |
Khorrami M, Jain P, Khunger M, Ahmad U, Stephans KL, Murthy SC, Velcheti V, Madabhushi A. Combination of CT derived radiomic features and lymphovascular invasion status to predict disease recurrence following trimodality therapy in non-small cell lung cancer. Journal of Clinical Oncology. 36: e24314-e24314. DOI: 10.1200/Jco.2018.36.15_Suppl.E24314 |
0.326 |
|
| 2018 |
Braman N, Ravichandran K, Janowczyk A, Abraham J, Madabhushi A. Predicting neo-adjuvant chemotherapy response from pre-treatment breast MRI using machine learning and HER2 status. Journal of Clinical Oncology. 36: 582-582. DOI: 10.1200/Jco.2018.36.15_Suppl.582 |
0.706 |
|
| 2018 |
Verma N, Harding D, Mohammadi A, Goldstein LJ, Gilmore HL, Feldman MD, Tomaszewski J, Basavanhally A, Lloyd M, Fu P, Ganesan S, Davidson NE, Madabhushi A, Monaco J. Image-based risk score to predict recurrence of ER+ breast cancer in ECOG-ACRIN Cancer Research Group E2197. Journal of Clinical Oncology. 36: 540-540. DOI: 10.1200/Jco.2018.36.15_Suppl.540 |
0.762 |
|
| 2018 |
Barrera C, Velu P, Bera K, Wang X, Prasanna P, Khunger M, Khunger A, Velcheti V, Romero E, Madabhushi A. Computer-extracted features relating to spatial arrangement of tumor infiltrating lymphocytes to predict response to nivolumab in non-small cell lung cancer (NSCLC). Journal of Clinical Oncology. 36: 12115-12115. DOI: 10.1200/Jco.2018.36.15_Suppl.12115 |
0.307 |
|
| 2018 |
Bhargava HK, Leo P, Elliott R, Janowczyk A, Whitney J, Gupta S, Yamoah K, Rebbeck T, Feldman MD, Lal P, Madabhushi A. Computer-extracted stromal features of African-Americans versus Caucasians from H&E slides and impact on prognosis of biochemical recurrence. Journal of Clinical Oncology. 36: 12075-12075. DOI: 10.1200/Jco.2018.36.15_Suppl.12075 |
0.677 |
|
| 2018 |
Li H, Whitney J, Thawani R, Gilmore H, Badve S, Madabhushi A. Abstract P4-09-12: Quantitative image features of nuclear and tubule architecture distinguish high and low oncotype DX risk categories of ductal carcinoma in situ from H&E tissue images Cancer Research. 78. DOI: 10.1158/1538-7445.Sabcs17-P4-09-12 |
0.457 |
|
| 2018 |
Whitney J, Romeo-Bucheli D, Janowczyk A, Ganesan S, Feldman M, Gilmore H, Madabhushi A. Abstract P4-09-11: Computer extracted features of tumor grade from H&E images predict oncotype DX risk categories for early stage ER+ breast cancer Cancer Research. 78. DOI: 10.1158/1538-7445.Sabcs17-P4-09-11 |
0.711 |
|
| 2018 |
Braman N, Prasanna P, Singh S, Beig N, Gilmore H, Etesami M, Bates D, Gallagher K, Bloch B, Somlo G, Sikov W, Harris L, Plecha D, Varadan V, Madabhushi A. Abstract P4-02-07: Radiogenomic analysis of HER2+ breast cancer reveals MRI features correlated with genomic immune index are predictive of neoadjuvant chemotherapy response Cancer Research. 78. DOI: 10.1158/1538-7445.Sabcs17-P4-02-07 |
0.443 |
|
| 2018 |
Braman N, Prasanna P, Singh S, Beig N, Gilmore H, Etesami M, Bates D, Gallagher K, Bloch B, Somlo G, Sikov W, Harris L, Plecha D, Varadan V, Madabhushi A. Abstract P4-02-06: Intratumoral and peritumoral MRI signatures of HER2-enriched subtype also predict pathological response to neoadjuvant chemotherapy in HER2+ breast cancers Cancer Research. 78. DOI: 10.1158/1538-7445.Sabcs17-P4-02-06 |
0.349 |
|
| 2018 |
Leo P, Shankar E, Elliott R, Janowczyk A, Janaki N, MacLennan GT, Madabhushi A, Gupta S. Abstract LB-021: Combination of quantitative histomorphometry with NFκB/p65 nuclear localization is better predictor of biochemical recurrence in prostate cancer patients Cancer Research. 78. DOI: 10.1158/1538-7445.Am2018-Lb-021 |
0.729 |
|
| 2018 |
Ismail M, Hill V, Statsevych V, Huang R, Correa R, Singh G, Bera K, Thawani R, Madabhushi A, Ahluwalia M, Tiwari P. NIMG-54. SPATIAL DISTRIBUTION ATLASES OF POST-TREATMENT MRI SCANS REVEAL DISTINCT HEMISPHERIC DISTRIBUTION OF GLIOBLASTOMA RECURRENCE FROM PSEUDO-PROGRESSION Neuro-Oncology. 20: vi188-vi188. DOI: 10.1093/Neuonc/Noy148.780 |
0.521 |
|
| 2018 |
Beig N, Braman N, Prasanna P, Varadan V, Madabhushi A, Tiwari P. NIMG-27. RADIOGENOMIC ANALYSIS OF GLIOBLASTOMA REVEALS TEXTURAL FEATURES FROM MRI THAT CORRELATE WITH GENOMIC IMMUNE SCORE AND ARE ALSO PREDICTIVE OF CHEMO-RADIATION TREATMENT RESPONSE Neuro-Oncology. 20: vi181-vi181. DOI: 10.1093/Neuonc/Noy148.753 |
0.548 |
|
| 2018 |
Beig N, Prasanna P, Verma R, Hill V, Varadan V, Madabhushi A, Tiwari P. NIMG-26. RADIOMIC FEATURES OF GLIOBLASTOMA ON PRE-TREATMENT GD-T1W MRI ARE PREDICTIVE OF RESPONSE TO CHEMO-RADIATION THERAPY AND ASSOCIATED WITH AKT AND APOPTOSIS PATHWAYS Neuro-Oncology. 20: vi181-vi181. DOI: 10.1093/Neuonc/Noy148.752 |
0.538 |
|
| 2018 |
Antunes J, Selvam A, Bera K, Brady J, Willis J, Paspulati Rm, Madabhushi A, Delaney CP, Viswanath S. 857 - Machine Learning Analysis of the Whole Rectal Wall on Post-Neoadjuvant Chemoradiation MRI may offer Accurate Identifiction of Rectal Cancer Patients Needing more Aggressive Follow-Up or Surgery Gastroenterology. 154: S-1289. DOI: 10.1016/S0016-5085(18)34228-8 |
0.674 |
|
| 2018 |
Chandramouli S, Leo P, Lee G, Elliott R, Zhu G, Veltri R, Madabhushi A. MP12-17 COMPUTER EXTRACTED FEATURES OF NUCLEI SHAPE, ARCHITECTURE AND ORIENTATION FROM INITIAL H&E TISSUE BIOPSIES PREDICT DISEASE PROGRESSION FOR PROSTATE CANCER PATIENTS ON ACTIVE SURVEILLANCE Journal of Urology. 199. DOI: 10.1016/J.Juro.2018.02.404 |
0.408 |
|
| 2018 |
Li H, Leo P, Nezami B, Akgul M, Elliott R, Harper H, Janowczyk A, MacLennan G, Madabhushi A. MP08-16 COMBINATION OF NUCLEAR ORIENTATION AND SHAPE FEATURES IN H&E STAINED IMAGES DISTINGUISH CONSENSUS LOW AND HIGH GRADE BLADDER CANCER Journal of Urology. 199. DOI: 10.1016/J.Juro.2018.02.321 |
0.722 |
|
| 2018 |
Leo P, Shankar E, Elliott R, Janowczyk A, Janaki N, MacLennan G, Madabhushi A, Gupta S. MP35-09 COMBINATION OF NF-κB/P65 NUCLEAR LOCALIZATION AND GLAND MORPHOLOGIC FEATURES IS PREDICTIVE OF BIOCHEMICAL RECURRENCE Journal of Urology. 199. DOI: 10.1016/J.Juro.2018.02.1122 |
0.655 |
|
| 2018 |
Leo P, Gawlik A, Zhu G, Feldman M, Gupta S, Veltri R, Madabhushi A. MP35-02 COMPUTER-EXTRACTED FEATURES OF NUCLEAR AND GLANDULAR MORPHOLOGY FROM DIGITAL H&E TISSUE IMAGES PREDICT PROSTATE CANCER BIOCHEMICAL RECURRENCE AND METASTASIS FOLLOWING RADICAL PROSTATECTOMY Journal of Urology. 199. DOI: 10.1016/J.Juro.2018.02.1115 |
0.462 |
|
| 2018 |
Li L, Jambor I, Taimen P, Merisaar H, Minn H, Bostrom P, Aronen H, Algohary A, Madabhushi A. MP35-01 PROSTATE TUMOR TEXTURAL HETEROGENEITY OF
11
C-ACETATE POSITRON EMISSION TOMOGRAPHY AND T2-WEIGHTED MAGNETIC RESONANCE IMAGING CORRELATE WITH BIOCHEMICAL RECURRENCE: PRELIMINARY FINDINGS Journal of Urology. 199. DOI: 10.1016/J.Juro.2018.02.1114 |
0.401 |
|
| 2017 |
Ghose S, Shiradkar R, Rusu M, Mitra J, Thawani R, Feldman M, Gupta AC, Purysko AS, Ponsky L, Madabhushi A. Prostate shapes on pre-treatment MRI between prostate cancer patients who do and do not undergo biochemical recurrence are different: Preliminary Findings. Scientific Reports. 7: 15829. PMID 29158516 DOI: 10.1038/S41598-017-13443-8 |
0.415 |
|
| 2017 |
Martel AL, Hosseinzadeh D, Senaras C, Zhou Y, Yazdanpanah A, Shojaii R, Patterson ES, Madabhushi A, Gurcan MN. An Image Analysis Resource for Cancer Research: PIIP-Pathology Image Informatics Platform for Visualization, Analysis, and Management. Cancer Research. 77: e83-e86. PMID 29092947 DOI: 10.1158/0008-5472.Can-17-0323 |
0.411 |
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| 2017 |
Wang X, Janowczyk A, Zhou Y, Thawani R, Fu P, Schalper K, Velcheti V, Madabhushi A. Prediction of recurrence in early stage non-small cell lung cancer using computer extracted nuclear features from digital H&E images. Scientific Reports. 7: 13543. PMID 29051570 DOI: 10.1038/S41598-017-13773-7 |
0.696 |
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| 2017 |
Wang H, Viswanath S, Madabhushi A. Discriminative Scale Learning (DiScrn): Applications to Prostate Cancer Detection from MRI and Needle Biopsies. Scientific Reports. 7: 12375. PMID 28959011 DOI: 10.1038/S41598-017-12569-Z |
0.739 |
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| 2017 |
Li L, Pahwa S, Penzias G, Rusu M, Gollamudi J, Viswanath S, Madabhushi A. Co-Registration of ex vivo Surgical Histopathology and in vivo T2 weighted MRI of the Prostate via multi-scale spectral embedding representation. Scientific Reports. 7: 8717. PMID 28821786 DOI: 10.1038/S41598-017-08969-W |
0.737 |
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| 2017 |
Singanamalli A, Wang H, Madabhushi A. Cascaded Multi-view Canonical Correlation (CaMCCo) for Early Diagnosis of Alzheimer's Disease via Fusion of Clinical, Imaging and Omic Features. Scientific Reports. 7: 8137. PMID 28811553 DOI: 10.1038/S41598-017-03925-0 |
0.385 |
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| 2017 |
Lu C, Lewis JS, Dupont WD, Plummer WD, Janowczyk A, Madabhushi A. An oral cavity squamous cell carcinoma quantitative histomorphometric-based image classifier of nuclear morphology can risk stratify patients for disease-specific survival. Modern Pathology : An Official Journal of the United States and Canadian Academy of Pathology, Inc. PMID 28776575 DOI: 10.1038/Modpathol.2017.98 |
0.714 |
|
| 2017 |
Braman NM, Etesami M, Prasanna P, Dubchuk C, Gilmore H, Tiwari P, Plecha D, Madabhushi A. Erratum to: Intratumoral and peritumoral radiomics for the pretreatment prediction of pathological complete response to neoadjuvant chemotherapy based on breast DCE-MRI. Breast Cancer Research : Bcr. 19: 80. PMID 28693537 DOI: 10.1186/S13058-017-0862-1 |
0.56 |
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| 2017 |
Gurcan MN, Tomaszewski JE, Madabhushi A. Special Section Guest Editorial: Digital Pathology. Journal of Medical Imaging (Bellingham, Wash.). 4: 021101. PMID 28680908 DOI: 10.1117/1.Jmi.4.2.021101 |
0.331 |
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| 2017 |
Prasanna P, Patel J, Partovi S, Madabhushi A, Tiwari P. Erratum to: Radiomic features from the peritumoral brain parenchyma on treatment-naïve multi-parametric MR imaging predict long versus short-term survival in glioblastoma multiforme: Preliminary findings. European Radiology. PMID 28608160 DOI: 10.1007/s00330-017-4815-y |
0.546 |
|
| 2017 |
Braman NM, Etesami M, Prasanna P, Dubchuk C, Gilmore H, Tiwari P, Pletcha D, Madabhushi A. Intratumoral and peritumoral radiomics for the pretreatment prediction of pathological complete response to neoadjuvant chemotherapy based on breast DCE-MRI. Breast Cancer Research : Bcr. 19: 57. PMID 28521821 DOI: 10.1186/S13058-017-0846-1 |
0.61 |
|
| 2017 |
Cruz-Roa A, Gilmore H, Basavanhally A, Feldman M, Ganesan S, Shih NNC, Tomaszewski J, González FA, Madabhushi A. Accurate and reproducible invasive breast cancer detection in whole-slide images: A Deep Learning approach for quantifying tumor extent. Scientific Reports. 7: 46450. PMID 28418027 DOI: 10.1038/Srep46450 |
0.799 |
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| 2017 |
Rusu M, Rajiah P, Gilkeson R, Yang M, Donatelli C, Thawani R, Jacono FJ, Linden P, Madabhushi A. Co-registration of pre-operative CT with ex vivo surgically excised ground glass nodules to define spatial extent of invasive adenocarcinoma on in vivo imaging: a proof-of-concept study. European Radiology. PMID 28386717 DOI: 10.1007/S00330-017-4813-0 |
0.311 |
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| 2017 |
Xu J, Monaco JP, Sparks R, Madabhushi A. Connecting Markov random fields and active contour models: application to gland segmentation and classification. Journal of Medical Imaging (Bellingham, Wash.). 4: 021107. PMID 28382316 DOI: 10.1117/1.Jmi.4.2.021107 |
0.412 |
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| 2017 |
Corredor G, Whitney J, Arias V, Madabhushi A, Romero E. Training a cell-level classifier for detecting basal-cell carcinoma by combining human visual attention maps with low-level handcrafted features. Journal of Medical Imaging (Bellingham, Wash.). 4: 021105. PMID 28382314 DOI: 10.1117/1.Jmi.4.2.021105 |
0.448 |
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| 2017 |
Alilou M, Beig N, Orooji M, Madabhushi A, Rajiah P, Yang M, Gilkeson R, Linden P, Velcheti V, Rakshit S, Reddy N, Jacono F. An integrated segmentation and shape based classification scheme for distinguishing adenocarcinomas from granulomas on lung CT. Medical Physics. PMID 28295386 DOI: 10.1002/Mp.12208 |
0.345 |
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| 2017 |
Romo-Bucheli D, Janowczyk A, Gilmore H, Romero E, Madabhushi A. A deep learning based strategy for identifying and associating mitotic activity with gene expression derived risk categories in estrogen receptor positive breast cancers. Cytometry. Part a : the Journal of the International Society For Analytical Cytology. PMID 28192639 DOI: 10.1002/Cyto.A.23065 |
0.71 |
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| 2017 |
Rusu M, Purysko AS, Verma S, Kiechle J, Gollamudi J, Ghose S, Herrmann K, Gulani V, Paspulati R, Ponsky L, Böhm M, Haynes AM, Moses D, Shnier R, Delprado W, ... ... Madabhushi A, et al. Computational imaging reveals shape differences between normal and malignant prostates on MRI. Scientific Reports. 7: 41261. PMID 28145532 DOI: 10.1038/Srep41261 |
0.421 |
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| 2017 |
Viswanath SE, Tiwari P, Lee G, Madabhushi A. Dimensionality reduction-based fusion approaches for imaging and non-imaging biomedical data: concepts, workflow, and use-cases. Bmc Medical Imaging. 17: 2. PMID 28056889 DOI: 10.1186/S12880-016-0172-6 |
0.753 |
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| 2017 |
Kim JJ, Bennett NK, Devita MS, Chahar S, Viswanath S, Lee EA, Jung G, Shao PP, Childers EP, Liu S, Kulesa A, Garcia BA, Becker ML, Hwang NS, Madabhushi A, et al. Optical High Content Nanoscopy of Epigenetic Marks Decodes Phenotypic Divergence in Stem Cells. Scientific Reports. 7: 39406. PMID 28051095 DOI: 10.1038/Srep39406 |
0.649 |
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| 2017 |
Lu C, Khunger M, Thawani R, Velcheti V, Madabhushi A. Computer extracted measurements of intra-tumoral heterogeneity on H&E stained tissue images to distinguish short term and long term survivors in patients with non-small cell lung carcinoma. Journal of Clinical Oncology. 35: e20052-e20052. DOI: 10.1200/Jco.2017.35.15_Suppl.E20052 |
0.427 |
|
| 2017 |
Lu C, Lewis J, Madabhushi A. Computer extracted features of nuclear architecture in H&E sections to predict disease recurrence in oropharyngeal squamous cell carcinoma patients. Journal of Clinical Oncology. 35: e17536-e17536. DOI: 10.1200/Jco.2017.35.15_Suppl.E17536 |
0.384 |
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| 2017 |
Ghose S, Shiradkar R, Rusu M, Mitra J, Thawani R, Gupta A, Purysko A, Madabhushi A. Computer extracted shape features of prostate capsule from MRI to predict biochemical recurrence of prostate cancer post-treatment. Journal of Clinical Oncology. 35: e16579-e16579. DOI: 10.1200/Jco.2017.35.15_Suppl.E16579 |
0.484 |
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| 2017 |
Leo P, Janaki N, Thawani R, Elliott R, Gupta S, Shih N, Feldman MD, Madabhushi A. Computer extracted features of gland morphology on H&E surgically resected tissue images as predictive of biochemical recurrence and rate of expression in African American compared to Caucasian American men. Journal of Clinical Oncology. 35: e16559-e16559. DOI: 10.1200/Jco.2017.35.15_Suppl.E16559 |
0.412 |
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| 2017 |
Gawlik A, Lee G, Feldman MD, Zhu G, Veltri RW, Madabhushi A. Computer extracted nuclear features from tumor and benign regions of Feulgen and H&E images to help predict recurrence in prostate cancer patients following radical prostatectomy. Journal of Clinical Oncology. 35: e16556-e16556. DOI: 10.1200/Jco.2017.35.15_Suppl.E16556 |
0.438 |
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| 2017 |
Shiradkar R, Ghose S, Purysko A, Madabhushi A. A combination of computer extracted measurements of prostate capsule shape and tumor texture on MRI to predict biochemical recurrence post treatment. Journal of Clinical Oncology. 35: e16554-e16554. DOI: 10.1200/Jco.2017.35.15_Suppl.E16554 |
0.416 |
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| 2017 |
Xie Y, Khunger M, Thawani R, Velcheti V, Madabhushi A. Evolution of radiomic features on serial CT scans as an imaging based biomarker for evaluating response in patients with non-small cell lung cancer treated with nivolumab. Journal of Clinical Oncology. 35: e14534-e14534. DOI: 10.1200/Jco.2017.35.15_Suppl.E14534 |
0.394 |
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| 2017 |
Khunger M, Alilou M, Thawani R, Madabhushi A, Velcheti V. Computer extracted measurements of vessel tortuosity on baseline CT scans to predict response to nivolumab immunotherapy for non-small cell lung cancer. Journal of Clinical Oncology. 35: 11566-11566. DOI: 10.1200/Jco.2017.35.15_Suppl.11566 |
0.341 |
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| 2017 |
Velcheti V, Alilou M, Khunger M, Thawani R, Madabhushi A. Changes in computer extracted features of vessel tortuosity on CT scans post-treatment in responders compared to non-responders for non-small cell lung cancer on immunotherapy. Journal of Clinical Oncology. 35: 11518-11518. DOI: 10.1200/Jco.2017.35.15_Suppl.11518 |
0.354 |
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| 2017 |
Shankar E, Kanwal R, Goel A, Yang X, Shukla S, MacLennan GT, Fu P, Madabhushi A, Ramakrishnan P, Gupta S. Abstract 1080: Targeting the PI3K-Akt and NF-κB pathways as a combination therapy in blocking prostate cancer progression Cancer Research. 77: 1080-1080. DOI: 10.1158/1538-7445.Am2017-1080 |
0.343 |
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| 2017 |
Beig N, Patel J, Prasanna P, Partovi S, Varadan V, Madabhushi A, Tiwari P. Radiogenomic analysis of hypoxia pathway reveals computerized MRI descriptors predictive of overall survival in glioblastoma Proceedings of Spie. 10134. DOI: 10.1117/12.2255694 |
0.613 |
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| 2017 |
Isamail M, Prasanna P, Huang R, Singh G, Thawani R, Madabhushi A, Ahluwalia M, Tiwari P. NIMG-80. SHAPE ATTRIBUTES OF ENHANCING LESION BOUNDARIES CAN DIFFERENTIATE TUMOR RECURRENCE FROM PSEUDO-PROGRESSION ON ROUTINE BRAIN MRI SCANS: PRELIMINARY FINDINGS Neuro-Oncology. 19: vi160-vi160. DOI: 10.1093/Neuonc/Nox168.651 |
0.587 |
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| 2017 |
Karnawat A, Prasanna P, Madabhushi A, Tiwari P. NIMG-61. USE OF TEXTURAL RADIOMIC MAPS IN A 3D CONVOLUTIONAL NEURAL NETWORK FRAMEWORK CAN AUGMENT GLIOMA LESION SEGMENTATION Neuro-Oncology. 19: vi156-vi156. DOI: 10.1093/Neuonc/Nox168.634 |
0.518 |
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| 2017 |
Prasanna P, Mitra J, Beig N, Partovi S, Singh G, Pinho M, Madabhushi A, Tiwari P. NIMG-17. STRUCTURAL DEFORMATION FIELD ON T1W MRI IN HEALTHY BRAIN PARENCHYMA IS ASSOCIATED WITH OVERALL SURVIVAL IN TREATMENT-NAÏVE GLIOBLASTOMA MULTIFORME Neuro-Oncology. 19: vi145-vi146. DOI: 10.1093/Neuonc/Nox168.595 |
0.518 |
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| 2017 |
Beig N, Correa R, Thawani R, Prasanna P, Badve C, Gold D, Madabhushi A, deBlank P, Tiwari P. MEDU-48. MRI TEXTURAL FEATURES CAN DIFFERENTIATE PEDIATRIC POSTERIOR FOSSA TUMORS Neuro-Oncology. 19: iv47-iv47. DOI: 10.1093/Neuonc/Nox083.197 |
0.571 |
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| 2017 |
Shiradkar R, Ghose S, Villani R, Ben-Levi E, Rastinehad A, Madabhushi A. PD65-08 DISTINGUISHING LOW VERSUS HIGH RISK PROSTATE CANCER LESIONS USING RADIOMIC FEATURES DERIVED FROM MULTI-PARAMETRIC MAGNETIC RESONANCE IMAGING (MRI) Journal of Urology. 197. DOI: 10.1016/J.Juro.2017.02.2958 |
0.44 |
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| 2017 |
Vaidya P, Patil P, Choi H, Velcheti V, Madabhushi A. PUB082 Radiomic Features on Baseline CT Are Predictive of Recurrence in Early Stage Non-Small Cell Lung Cancer Patients Journal of Thoracic Oncology. 12: S2393. DOI: 10.1016/J.Jtho.2017.09.1945 |
0.321 |
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| 2017 |
Wang X, Corredor G, Romero E, Schalper K, Yang M, Rimm D, Velcheti V, Madabhushi A. PUB024 Clusters Spatial Arrangement of Tumor Infiltrating Lymphocyte and Cancer Nuclei Predicts Recurrence in Early Stage Non-Small Cell Lung Cancer Journal of Thoracic Oncology. 12: S2372-S2373. DOI: 10.1016/J.Jtho.2017.09.1887 |
0.314 |
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| 2017 |
Cardoso MJ, Arbel T, Carneiro G, Syeda-Mahmood T, Tavares JMRS, Moradi M, Bradley A, Greenspan H, Papa JP, Madabhushi A, Nascimento JC, Cardoso JS, Belagiannis V, Lu Z, Engenharia Fd. Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support Arxiv: Computer Vision and Pattern Recognition. DOI: 10.1007/978-3-319-67558-9 |
0.417 |
|
| 2016 |
Lee G, Veltri RW, Zhu G, Ali S, Epstein JI, Madabhushi A. Nuclear Shape and Architecture in Benign Fields Predict Biochemical Recurrence in Prostate Cancer Patients Following Radical Prostatectomy: Preliminary Findings. European Urology Focus. PMID 28753763 DOI: 10.1016/J.Euf.2016.05.009 |
0.396 |
|
| 2016 |
Xu J, Luo X, Wang G, Gilmore H, Madabhushi A. A Deep Convolutional Neural Network for segmenting and classifying epithelial and stromal regions in histopathological images. Neurocomputing. 191: 214-223. PMID 28154470 DOI: 10.1016/J.Neucom.2016.01.034 |
0.461 |
|
| 2016 |
Ginsburg SB, Algohary A, Pahwa S, Gulani V, Ponsky L, Aronen HJ, Boström PJ, Böhm M, Haynes AM, Brenner P, Delprado W, Thompson J, Pulbrock M, Taimen P, Villani R, ... ... Madabhushi A, et al. Radiomic features for prostate cancer detection on MRI differ between the transition and peripheral zones: Preliminary findings from a multi-institutional study. Journal of Magnetic Resonance Imaging : Jmri. PMID 27990722 DOI: 10.1002/Jmri.25562 |
0.434 |
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| 2016 |
Prasanna P, Tiwari P, Madabhushi A. Co-occurrence of Local Anisotropic Gradient Orientations (CoLlAGe): A new radiomics descriptor. Scientific Reports. 6: 37241. PMID 27872484 DOI: 10.1038/Srep37241 |
0.647 |
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| 2016 |
Shiradkar R, Podder TK, Algohary A, Viswanath S, Ellis RJ, Madabhushi A. Radiomics based targeted radiotherapy planning (Rad-TRaP): a computational framework for prostate cancer treatment planning with MRI. Radiation Oncology (London, England). 11: 148. PMID 27829431 DOI: 10.1186/S13014-016-0718-3 |
0.698 |
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| 2016 |
Leo P, Lee G, Shih NN, Elliott R, Feldman MD, Madabhushi A. Evaluating stability of histomorphometric features across scanner and staining variations: prostate cancer diagnosis from whole slide images. Journal of Medical Imaging (Bellingham, Wash.). 3: 047502. PMID 27803941 DOI: 10.1117/1.Jmi.3.4.047502 |
0.498 |
|
| 2016 |
Prasanna P, Patel J, Partovi S, Madabhushi A, Tiwari P. Radiomic features from the peritumoral brain parenchyma on treatment-naïve multi-parametric MR imaging predict long versus short-term survival in glioblastoma multiforme: Preliminary findings. European Radiology. PMID 27778090 DOI: 10.1007/S00330-016-4637-3 |
0.583 |
|
| 2016 |
Tiwari P, Prasanna P, Wolansky L, Pinho M, Cohen M, Nayate AP, Gupta A, Singh G, Hattanpaa K, Sloan A, Rogers L, Madabhushi A. Computer-Extracted Texture Features to Distinguish Cerebral Radionecrosis from Recurrent Brain Tumors on Multiparametric MRI: A Feasibility Study. Ajnr. American Journal of Neuroradiology. PMID 27633806 DOI: 10.3174/Ajnr.A4931 |
0.599 |
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| 2016 |
Romo-Bucheli D, Janowczyk A, Gilmore H, Romero E, Madabhushi A. Automated Tubule Nuclei Quantification and Correlation with Oncotype DX risk categories in ER+ Breast Cancer Whole Slide Images. Scientific Reports. 6: 32706. PMID 27599752 DOI: 10.1117/12.2211368 |
0.702 |
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| 2016 |
Janowczyk A, Madabhushi A. Deep learning for digital pathology image analysis: A comprehensive tutorial with selected use cases. Journal of Pathology Informatics. 7: 29. PMID 27563488 DOI: 10.4103/2153-3539.186902 |
0.722 |
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| 2016 |
Penzias G, Janowczyk A, Singanamalli A, Rusu M, Shih N, Feldman M, Stricker PD, Delprado W, Tiwari S, Böhm M, Haynes AM, Ponsky L, Viswanath S, Madabhushi A. AutoStitcher: An Automated Program for Efficient and Robust Reconstruction of Digitized Whole Histological Sections from Tissue Fragments. Scientific Reports. 6: 29906. PMID 27457670 DOI: 10.1038/Srep29906 |
0.789 |
|
| 2016 |
Madabhushi A, Lee G. Image analysis and machine learning in digital pathology: Challenges and opportunities. Medical Image Analysis. PMID 27423409 DOI: 10.1016/J.Media.2016.06.037 |
0.492 |
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| 2016 |
Lee G, Romo Bucheli DE, Madabhushi A. Adaptive Dimensionality Reduction with Semi-Supervision (AdDReSS): Classifying Multi-Attribute Biomedical Data. Plos One. 11: e0159088. PMID 27421116 DOI: 10.1371/Journal.Pone.0159088 |
0.404 |
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| 2016 |
Bhargava R, Madabhushi A. Emerging Themes in Image Informatics and Molecular Analysis for Digital Pathology. Annual Review of Biomedical Engineering. 18: 387-412. PMID 27420575 DOI: 10.1146/Annurev-Bioeng-112415-114722 |
0.407 |
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| 2016 |
Janowczyk A, Basavanhally A, Madabhushi A. Stain Normalization using Sparse AutoEncoders (StaNoSA): Application to digital pathology. Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society. PMID 27373749 DOI: 10.1016/J.Compmedimag.2016.05.003 |
0.816 |
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| 2016 |
Ginsburg SB, Taimen P, Merisaari H, Vainio P, Boström PJ, Aronen HJ, Jambor I, Madabhushi A. Patient-specific pharmacokinetic parameter estimation on dynamic contrast-enhanced MRI of prostate: Preliminary evaluation of a novel AIF-free estimation method. Journal of Magnetic Resonance Imaging : Jmri. PMID 27285161 DOI: 10.1002/Jmri.25330 |
0.387 |
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| 2016 |
Sparks R, Madabhushi A. Out-of-Sample Extrapolation utilizing Semi-Supervised Manifold Learning (OSE-SSL): Content Based Image Retrieval for Histopathology Images. Scientific Reports. 6: 27306. PMID 27264985 DOI: 10.1038/Srep27306 |
0.492 |
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| 2016 |
Toth R, Sperling D, Madabhushi A. Quantifying Post- Laser Ablation Prostate Therapy Changes on MRI via a Domain-Specific Biomechanical Model: Preliminary Findings. Plos One. 11: e0150016. PMID 27088600 DOI: 10.1371/Journal.Pone.0150016 |
0.361 |
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| 2016 |
Antunes J, Viswanath S, Rusu M, Valls L, Hoimes C, Avril N, Madabhushi A. Radiomics Analysis on FLT-PET/MRI for Characterization of Early Treatment Response in Renal Cell Carcinoma: A Proof-of-Concept Study. Translational Oncology. 9: 155-62. PMID 27084432 DOI: 10.1016/J.Tranon.2016.01.008 |
0.703 |
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| 2016 |
Wan T, Bloch BN, Plecha D, Thompson CL, Gilmore H, Jaffe C, Harris L, Madabhushi A. A Radio-genomics Approach for Identifying High Risk Estrogen Receptor-positive Breast Cancers on DCE-MRI: Preliminary Results in Predicting OncotypeDX Risk Scores. Scientific Reports. 6: 21394. PMID 26887643 DOI: 10.1038/Srep21394 |
0.436 |
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| 2016 |
Braman N, Prasanna P, Plecha D, Gilmore HL, Harris L, Varadan V, Madabhushi A. Computerized textural analysis of DCE-MRI to enable identification of HER2-enriched breast cancers. Journal of Clinical Oncology. 34: 598-598. DOI: 10.1200/Jco.2016.34.15_Suppl.598 |
0.413 |
|
| 2016 |
Gawlik A, Lee G, Epstein JI, Veltri RW, Zhu G, Pienta KJ, Madabhushi A. Computer extracted nuclear features from Feulgen and H&E images to predict biochemical recurrence in prostate cancer patients following radical prostatectomy. Journal of Clinical Oncology. 34: 5067-5067. DOI: 10.1200/Jco.2016.34.15_Suppl.5067 |
0.438 |
|
| 2016 |
Orooji M, Rakshit S, Beig N, Madabhushi A, Velcheti V. Computerized textural analysis of lung CT to enable quantification of tumor infiltrating lymphocytes in NSCLC. Journal of Clinical Oncology. 34: 11584-11584. DOI: 10.1200/Jco.2016.34.15_Suppl.11584 |
0.389 |
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| 2016 |
Rakshit S, Orooji M, Beig N, Alilou M, Pennell NA, Stevenson J, Shapiro MA, Madabhushi A, Velcheti V. Evaluation of radiomic features on baseline CT scan to predict clinical benefit for pemetrexed based chemotherapy in metastatic lung adenocarcinoma. Journal of Clinical Oncology. 34: 11582-11582. DOI: 10.1200/Jco.2016.34.15_Suppl.11582 |
0.364 |
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| 2016 |
Lee G, Veltri RW, Zhu G, Epstein JI, Pienta KJ, Madabhushi A. Computer extracted features on H&E images to improve biochemical recurrence prediction of Kattan nomogram for prostate cancer patients following radical prostatectomy: Preliminary findings. Journal of Clinical Oncology. 34: 11556-11556. DOI: 10.1200/Jco.2016.34.15_Suppl.11556 |
0.435 |
|
| 2016 |
Ali S, Rimm D, Ganesan S, Madabhushi A. Abstract P5-07-12: Local nuclear architecture features from H&E images predict early versus distant recurrence in lymph node negative, ER+ breast cancers Cancer Research. 76. DOI: 10.1158/1538-7445.Sabcs15-P5-07-12 |
0.391 |
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| 2016 |
Li L, Rusu M, Viswanath S, Penzias G, Pahwa S, Gollamudi J, Madabhushi A. Multi-modality registration via multi-scale textural and spectral embedding representations Proceedings of Spie. 9784: 978446. DOI: 10.1117/12.2217639 |
0.735 |
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| 2016 |
Leo P, Lee G, Madabhushi A. Evaluating stability of histomorphometric features across scanner and staining variations: predicting biochemical recurrence from prostate cancer whole slide images Proceedings of Spie. 9791. DOI: 10.1117/12.2217053 |
0.476 |
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| 2016 |
Prasanna P, Rogers L, Cohen M, Singh G, Badve C, Wolansky L, Madabhushi A, Tiwari P. NIMG-75. FEATURES OF LOCAL GRADIENT DISORDER ON MRI THAT DISTINGUISH RADIATION NECROSIS AND TUMOR RECURRENCE POST-RADIOTHERAPY ARE ASSOCIATED WITH ZONAL NECROSIS, VESSEL WALL THICKENING, HYALINIZATION AND DEMYELINATION: A PRELIMINARY STUDY IN BRAIN TUMORS Neuro-Oncology. 18: vi141-vi141. DOI: 10.1093/Neuonc/Now212.586 |
0.548 |
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| 2016 |
Prasanna P, Nayate A, Gupta A, Rogers L, Singh G, Wolansky L, Pinho M, Hatanpaa K, Madabhushi A, Tiwari P. NIMG-69. DISTINGUISHING RADIATION NECROSIS FROM BRAIN TUMOR RECURRENCE ON ROUTINE MRI: A PRELIMINARY HUMAN-MACHINE READER COMPARISON STUDY Neuro-Oncology. 18: vi139-vi140. DOI: 10.1093/Neuonc/Now212.580 |
0.534 |
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| 2016 |
Mitra J, Nayate A, Madabhushi A, Tiwari P. NIMG-51. IMPACT ON REMOTE FUNCTIONAL AREAS DUE TO TUMOR MASS EFFECT IS PROGNOSTIC OF OVERALL SURVIVAL IN GLIOBLASTOMA MULTIFORME Neuro-Oncology. 18: vi135-vi135. DOI: 10.1093/Neuonc/Now212.562 |
0.509 |
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| 2016 |
Beig N, Correa R, Prasanna P, Mitra J, Madabhushi A, Nayate A, Tiwari P. NIMG-03. PREDICTING IDH MUTATION STATUS ON ROUTINE TREATMENT-NAÏVE MRI USING RADIOGENOMIC FEATURES FROM PERITUMORAL BRAIN PARENCHYMA Neuro-Oncology. 18: vi124-vi124. DOI: 10.1093/Neuonc/Now212.515 |
0.541 |
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| 2016 |
Madabhushi A. Computerized Histologic Image Based Risk Predictor (CHIRP): Identifying Disease Aggressiveness Using Sub-visual Image Cues from Image Data Microscopy and Microanalysis. 22: 1006-1007. DOI: 10.1017/S1431927616005870 |
0.3 |
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| 2016 |
Cohn H, Lu C, Paspulati RM, Katz J, Madabhushi A, Stein SL, Cominelli F, Viswanath S, Dave M. Tu1966 A Machine-Learning Based Risk Score to Predict Response to Therapy in Crohn's Disease via Baseline MRE Gastroenterology. 150: S992. DOI: 10.1016/S0016-5085(16)33359-5 |
0.635 |
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| 2016 |
Xu J, Luo X, Wang G, Gilmore H, Madabhushi A. A Deep Convolutional Neural Network for segmenting and classifying epithelial and stromal regions in histopathological images Neurocomputing. 191: 214-223. DOI: 10.1016/j.neucom.2016.01.034 |
0.352 |
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| 2016 |
Gawlik A, Lee G, Whitney J, Epstein J, Veltri R, Madabhushi A. MP02-17 COMPUTER EXTRACTED NUCLEAR FEATURES FROM FEULGEN AND H&E IMAGES PREDICT BIOCHEMICAL RECURRENCE IN PROSTATE CANCER PATIENTS FOLLOWING RADICAL PROSTATECTOMY Journal of Urology. 195. DOI: 10.1016/J.Juro.2016.02.1889 |
0.457 |
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| 2015 |
Tiwari P, Danish SF, Jiang B, Madabhushi A. Association of computerized texture features on MRI with early treatment response following laser ablation for neuropathic cancer pain: preliminary findings. Journal of Medical Imaging (Bellingham, Wash.). 2: 041008. PMID 26870745 DOI: 10.1117/1.Jmi.2.4.041008 |
0.614 |
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| 2015 |
Varadan V, Kamalakaran S, Gilmore H, Banerjee N, Janevski A, Miskimen KL, Williams N, Basavanhalli A, Madabhushi A, Lezon-Geyda K, Bossuyt V, Lannin DR, Abu-Khalaf M, Sikov W, Dimitrova N, et al. Brief-exposure to preoperative bevacizumab reveals a TGF-β signature predictive of response in HER2-negative breast cancers. International Journal of Cancer. Journal International Du Cancer. PMID 26284485 DOI: 10.1002/Ijc.29808 |
0.317 |
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| 2015 |
Rusu M, Golden T, Wang H, Gow A, Madabhushi A. Framework for 3D histologic reconstruction and fusion with in vivo MRI: Preliminary results of characterizing pulmonary inflammation in a mouse model. Medical Physics. 42: 4822-32. PMID 26233209 DOI: 10.1118/1.4923161 |
0.424 |
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| 2015 |
Xu J, Xiang L, Liu Q, Gilmore H, Wu J, Tang J, Madabhushi A. Stacked Sparse Autoencoder (SSAE) for Nuclei Detection on Breast Cancer Histopathology images. Ieee Transactions On Medical Imaging. PMID 26208307 DOI: 10.1109/Tmi.2015.2458702 |
0.499 |
|
| 2015 |
Litjens GJ, Elliott R, Shih NN, Feldman MD, Kobus T, Hulsbergen-van de Kaa C, Barentsz JO, Huisman HJ, Madabhushi A. Computer-extracted Features Can Distinguish Noncancerous Confounding Disease from Prostatic Adenocarcinoma at Multiparametric MR Imaging. Radiology. 142856. PMID 26192734 DOI: 10.1148/Radiol.2015142856 |
0.461 |
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| 2015 |
Ginsburg S, Lee G, Ali S, Madabhushi A. Feature Importance in Nonlinear Embeddings (FINE): Applications in Digital Pathology. Ieee Transactions On Medical Imaging. PMID 26186772 DOI: 10.1109/Tmi.2015.2456188 |
0.49 |
|
| 2015 |
Sridhar A, Doyle S, Madabhushi A. Content-based image retrieval of digitized histopathology in boosted spectrally embedded spaces. Journal of Pathology Informatics. 6: 41. PMID 26167385 DOI: 10.4103/2153-3539.159441 |
0.644 |
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| 2015 |
Singanamalli A, Rusu M, Sparks RE, Shih NN, Ziober A, Wang LP, Tomaszewski J, Rosen M, Feldman M, Madabhushi A. Identifying in vivo DCE MRI markers associated with microvessel architecture and gleason grades of prostate cancer. Journal of Magnetic Resonance Imaging : Jmri. PMID 26110513 DOI: 10.1002/Jmri.24975 |
0.424 |
|
| 2015 |
Basavanhally A, Viswanath S, Madabhushi A. Predicting classifier performance with limited training data: applications to computer-aided diagnosis in breast and prostate cancer. Plos One. 10: e0117900. PMID 25993029 DOI: 10.1371/Journal.Pone.0117900 |
0.832 |
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| 2015 |
Xu J, Xiang L, Wang G, Ganesan S, Feldman M, Shih NN, Gilmore H, Madabhushi A. Sparse Non-negative Matrix Factorization (SNMF) based color unmixing for breast histopathological image analysis. Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society. PMID 25958195 DOI: 10.1016/J.Compmedimag.2015.04.002 |
0.409 |
|
| 2015 |
Sparks R, Bloch BN, Feleppa E, Barratt D, Moses D, Ponsky L, Madabhushi A. Multiattribute probabilistic prostate elastic registration (MAPPER): application to fusion of ultrasound and magnetic resonance imaging. Medical Physics. 42: 1153-63. PMID 25735270 DOI: 10.1118/1.4905104 |
0.449 |
|
| 2015 |
Veta M, van Diest PJ, Willems SM, Wang H, Madabhushi A, Cruz-Roa A, Gonzalez F, Larsen AB, Vestergaard JS, Dahl AB, Cire?an DC, Schmidhuber J, Giusti A, Gambardella LM, Tek FB, et al. Assessment of algorithms for mitosis detection in breast cancer histopathology images. Medical Image Analysis. 20: 237-48. PMID 25547073 DOI: 10.1016/J.Media.2014.11.010 |
0.442 |
|
| 2015 |
Ali S, Veltri R, Epstein JI, Christudass C, Madabhushi A. Selective invocation of shape priors for deformable segmentation and morphologic classification of prostate cancer tissue microarrays. Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society. 41: 3-13. PMID 25466771 DOI: 10.1016/J.Compmedimag.2014.11.001 |
0.47 |
|
| 2015 |
Lee G, Singanamalli A, Wang H, Feldman MD, Master SR, Shih NN, Spangler E, Rebbeck T, Tomaszewski JE, Madabhushi A. Supervised multi-view canonical correlation analysis (sMVCCA): integrating histologic and proteomic features for predicting recurrent prostate cancer. Ieee Transactions On Medical Imaging. 34: 284-97. PMID 25203987 DOI: 10.1109/Tmi.2014.2355175 |
0.465 |
|
| 2015 |
Ginsburg SB, Viswanath SE, Bloch BN, Rofsky NM, Genega EM, Lenkinski RE, Madabhushi A. Novel PCA-VIP scheme for ranking MRI protocols and identifying computer-extracted MRI measurements associated with central gland and peripheral zone prostate tumors. Journal of Magnetic Resonance Imaging : Jmri. 41: 1383-93. PMID 24943647 DOI: 10.1002/Jmri.24676 |
0.728 |
|
| 2015 |
Zhu G, Lee G, Davis C, Kagohara LT, Epstein JI, Landis P, Carter HB, Madabhushi A, Veltri RW. Abstract 4352: Prediction of prostate cancer progression with biomarkers and tissue morphometry changes Cancer Research. 75: 4352-4352. DOI: 10.1158/1538-7445.Am2015-4352 |
0.437 |
|
| 2015 |
Veltri RW, Ali S, Lin W, Zhu G, Epstein JI, Li C, Madabhushi A. Abstract 4349: Cancer histologic and cell nucleus architecture differentiate prostate cancer Gleason patterns 3 from 4 Cancer Research. 75: 4349-4349. DOI: 10.1158/1538-7445.Am2015-4349 |
0.426 |
|
| 2015 |
Cruz-Roa A, Arévalo J, Judkins A, Madabhushi A, González F. A method for medulloblastoma tumor differentiation based on convolutional neural networks and transfer learning Proceedings of Spie - the International Society For Optical Engineering. 9681. DOI: 10.1117/12.2208825 |
0.325 |
|
| 2015 |
Cruz-Roa A, Xu J, Madabhushi A. A note on the stability and discriminability of graph based features for classification problems in digital pathology Progress in Biomedical Optics and Imaging - Proceedings of Spie. 9287. DOI: 10.1117/12.2085141 |
0.32 |
|
| 2015 |
Cruz-Roa A, Arevalo J, Basavanhally A, Madabhushi A, González F. A comparative evaluation of supervised and unsupervised representation learning approaches for anaplastic medulloblastoma differentiation Progress in Biomedical Optics and Imaging - Proceedings of Spie. 9287. DOI: 10.1117/12.2073849 |
0.728 |
|
| 2015 |
Tiwari P, Patel J, Partovi S, Prasanna P, Madabhushi A. NIMG-67COMPUTER EXTRACTED TEXTURE DESCRIPTORS FROM DIFFERENT TISSUE COMPARTMENTS WITHIN THE TUMOR HABITAT ON TREATMENT-NAÏVE MRI PREDICT CLINICAL SURVIVAL IN GLIOBLASTOMA PATIENTS Neuro-Oncology. 17: v169.3-v169. DOI: 10.1093/Neuonc/Nov225.67 |
0.585 |
|
| 2015 |
Prasanna P, Siddalingappa A, Wolansky L, Rogers L, Lam T, To V, Madabhushi A, Tiwari P. ATPS-67MORPHOLOGIC HETEROGENEITY AT A PIXEL-LEVEL CAPTURED VIA ENTROPY OF GRADIENT ORIENTATIONS ON T1-POST CONTRAST MRI ENABLES DISCRIMINATION OF TUMOR RECURRENCE FROM CEREBRAL RADIATION NECROSIS Neuro-Oncology. 17: v33.1-v33. DOI: 10.1093/Neuonc/Nov204.67 |
0.596 |
|
| 2015 |
Lee G, Veltri R, Ali S, Epstein J, Christudass C, Madabhushi A. MP6-18 PROSTATE CANCER RECURRENCE CAN BE PREDICTED BY MEASURING NUCLEAR ORGANIZATION AND SHAPE PARAMETERS IN ADJACENT BENIGN REGIONS ON RADICAL PROSTATECTOMY SPECIMENS Journal of Urology. 193. DOI: 10.1016/J.Juro.2015.02.265 |
0.377 |
|
| 2015 |
Algohary A, Viswanath S, Prasanna P, Pahwa S, Gulani V, Moses D, Shnier R, Böhm M, Haynes A, Brenner P, Delprado W, Thompson J, Pulbrock M, Stricker P, Ponsky L, ... Madabhushi A, et al. MP60-04 QUANTITATIVE ASSESSMENT OF T2-WEIGHTED MRI TO BETTER IDENTIFY PATIENTS WITH PROSTATE CANCER IN A SCREENING POPULATION Journal of Urology. 193. DOI: 10.1016/J.Juro.2015.02.2206 |
0.667 |
|
| 2015 |
Lee G, Veltri R, Zhu G, Carter HB, Landis P, Epstein J, Madabhushi A. MP1-15 QUANTITATIVE HISTOMORPHOMETRIC ANALYSIS OF PROSTATE BIOPSY IMAGES PREDICT FAVORABLE OUTCOME IN ACTIVE SURVEILLANCE PATIENTS Journal of Urology. 193. DOI: 10.1016/J.Juro.2015.02.178 |
0.423 |
|
| 2014 |
Litjens GJ, Huisman HJ, Elliott RM, Shih NN, Feldman MD, Viswanath S, Fütterer JJ, Bomers JG, Madabhushi A. Quantitative identification of magnetic resonance imaging features of prostate cancer response following laser ablation and radical prostatectomy. Journal of Medical Imaging (Bellingham, Wash.). 1: 035001. PMID 26158070 DOI: 10.1117/1.Jmi.1.3.035001 |
0.747 |
|
| 2014 |
Wang H, Cruz-Roa A, Basavanhally A, Gilmore H, Shih N, Feldman M, Tomaszewski J, Gonzalez F, Madabhushi A. Mitosis detection in breast cancer pathology images by combining handcrafted and convolutional neural network features. Journal of Medical Imaging (Bellingham, Wash.). 1: 034003. PMID 26158062 DOI: 10.1117/1.Jmi.1.3.034003 |
0.774 |
|
| 2014 |
Tiwari P, Danish S, Madabhushi A. Identifying MRI markers associated with early response following laser ablation for neurological disorders: preliminary findings. Plos One. 9: e114293. PMID 25503713 DOI: 10.1371/Journal.Pone.0114293 |
0.567 |
|
| 2014 |
Colen R, Foster I, Gatenby R, Giger ME, Gillies R, Gutman D, Heller M, Jain R, Madabhushi A, Madhavan S, Napel S, Rao A, Saltz J, Tatum J, Verhaak R, et al. NCI Workshop Report: Clinical and Computational Requirements for Correlating Imaging Phenotypes with Genomics Signatures. Translational Oncology. 7: 556-69. PMID 25389451 DOI: 10.1016/J.Tranon.2014.07.007 |
0.409 |
|
| 2014 |
Viswanath S, Toth R, Rusu M, Sperling D, Lepor H, Futterer J, Madabhushi A. Identifying Quantitative In Vivo Multi-Parametric MRI Features For Treatment Related Changes after Laser Interstitial Thermal Therapy of Prostate Cancer. Neurocomputing. 144: 13-23. PMID 25346574 DOI: 10.1016/J.Neucom.2014.03.065 |
0.745 |
|
| 2014 |
Wang H, Singanamalli A, Ginsburg S, Madabhushi A. Selecting features with group-sparse nonnegative supervised canonical correlation analysis: multimodal prostate cancer prognosis. Medical Image Computing and Computer-Assisted Intervention : Miccai ... International Conference On Medical Image Computing and Computer-Assisted Intervention. 17: 385-92. PMID 25320823 DOI: 10.1007/978-3-319-10443-0_49 |
0.32 |
|
| 2014 |
Prasanna P, Tiwari P, Madabhushi A. Co-occurrence of local anisotropic gradient orientations (CoLIAGe): distinguishing tumor confounders and molecular subtypes on MRI. Medical Image Computing and Computer-Assisted Intervention : Miccai ... International Conference On Medical Image Computing and Computer-Assisted Intervention. 17: 73-80. PMID 25320784 |
0.584 |
|
| 2014 |
Toth R, Traughber B, Ellis R, Kurhanewicz J, Madabhushi A. A Domain Constrained Deformable (DoCD) Model for Co-registration of Pre- and Post-Radiated Prostate MRI. Neurocomputing. 114: 3-12. PMID 25267873 DOI: 10.1016/J.Neucom.2014.01.058 |
0.407 |
|
| 2014 |
Wan T, Bloch BN, Danish S, Madabhushi A. A Learning Based Fiducial-driven Registration Scheme for Evaluating Laser Ablation Changes in Neurological Disorders. Neurocomputing. 144: 24-37. PMID 25225455 DOI: 10.1016/J.Neucom.2013.11.051 |
0.416 |
|
| 2014 |
Tiwari P, Danish S, Madabhushi A. Identifying MRI markers to evaluate early treatment related changes post laser ablation for cancer pain management. Proceedings of Spie--the International Society For Optical Engineering. 9036: 90362L. PMID 25075271 DOI: 10.1117/12.2043729 |
0.614 |
|
| 2014 |
Rusu M, Bloch BN, Jaffe CC, Genega EM, Lenkinski RE, Rofsky NM, Feleppa E, Madabhushi A. Prostatome: a combined anatomical and disease based MRI atlas of the prostate. Medical Physics. 41: 072301. PMID 24989400 DOI: 10.1118/1.4881515 |
0.464 |
|
| 2014 |
Lee G, Sparks R, Ali S, Shih NN, Feldman MD, Spangler E, Rebbeck T, Tomaszewski JE, Madabhushi A. Co-occurring gland angularity in localized subgraphs: predicting biochemical recurrence in intermediate-risk prostate cancer patients. Plos One. 9: e97954. PMID 24875018 DOI: 10.1371/Journal.Pone.0097954 |
0.454 |
|
| 2014 |
Toth RJ, Shih N, Tomaszewski JE, Feldman MD, Kutter O, Yu DN, Paulus JC, Paladini G, Madabhushi A. Histostitcher™: An informatics software platform for reconstructing whole-mount prostate histology using the extensible imaging platform framework. Journal of Pathology Informatics. 5: 8. PMID 24843820 DOI: 10.4103/2153-3539.129441 |
0.461 |
|
| 2014 |
Wan T, Madabhushi A, Phinikaridou A, Hamilton JA, Hua N, Pham T, Danagoulian J, Kleiman R, Buckler AJ. Spatio-temporal texture (SpTeT) for distinguishing vulnerable from stable atherosclerotic plaque on dynamic contrast enhancement (DCE) MRI in a rabbit model. Medical Physics. 41: 042303. PMID 24694153 DOI: 10.1118/1.4867861 |
0.317 |
|
| 2014 |
Agner SC, Rosen MA, Englander S, Tomaszewski JE, Feldman MD, Zhang P, Mies C, Schnall MD, Madabhushi A. Computerized image analysis for identifying triple-negative breast cancers and differentiating them from other molecular subtypes of breast cancer on dynamic contrast-enhanced MR images: a feasibility study. Radiology. 272: 91-9. PMID 24620909 DOI: 10.1148/Radiol.14121031 |
0.771 |
|
| 2014 |
Litjens G, Toth R, van de Ven W, Hoeks C, Kerkstra S, van Ginneken B, Vincent G, Guillard G, Birbeck N, Zhang J, Strand R, Malmberg F, Ou Y, Davatzikos C, Kirschner M, ... ... Madabhushi A, et al. Evaluation of prostate segmentation algorithms for MRI: the PROMISE12 challenge. Medical Image Analysis. 18: 359-73. PMID 24418598 DOI: 10.1016/J.Media.2013.12.002 |
0.429 |
|
| 2014 |
Lewis JS, Ali S, Luo J, Thorstad WL, Madabhushi A. A quantitative histomorphometric classifier (QuHbIC) identifies aggressive versus indolent p16-positive oropharyngeal squamous cell carcinoma. The American Journal of Surgical Pathology. 38: 128-37. PMID 24145650 DOI: 10.1097/Pas.0000000000000086 |
0.34 |
|
| 2014 |
Hwuang E, Rusu M, Karthigeyan S, Agner SC, Sparks R, Shih N, Tomaszewski JE, Rosen M, Feldman M, Madabhushi A. Spectral embedding-based registration (SERg) for multimodal fusion of prostate histology and MRI Progress in Biomedical Optics and Imaging - Proceedings of Spie. 9034. DOI: 10.1117/12.2044317 |
0.802 |
|
| 2014 |
Orooji M, Sparks R, Bloch BN, Feleppa E, Barratt D, Madabhushi A. Spatially aware expectation maximization (SpAEM): Application to prostate TRUS segmentation Progress in Biomedical Optics and Imaging - Proceedings of Spie. 9034. DOI: 10.1117/12.2043981 |
0.402 |
|
| 2014 |
Ginsburg SB, Rusu M, Kurhanewicz J, Madabhushi A. Computer extracted texture features on T2w MRI to predict biochemical recurrence following radiation therapy for prostate cancer Progress in Biomedical Optics and Imaging - Proceedings of Spie. 9035. DOI: 10.1117/12.2043937 |
0.466 |
|
| 2014 |
Wang H, Cruz-Roa A, Basavanhally A, Gilmore H, Shih N, Feldman M, Tomaszewski J, Gonzalez F, Madabhushi A. Cascaded ensemble of convolutional neural networks and handcrafted features for mitosis detection Progress in Biomedical Optics and Imaging - Proceedings of Spie. 9041. DOI: 10.1117/12.2043902 |
0.763 |
|
| 2014 |
Cruz-Roa A, Basavanhally A, González F, Gilmore H, Feldman M, Ganesan S, Shih N, Tomaszewski J, Madabhushi A. Automatic detection of invasive ductal carcinoma in whole slide images with convolutional neural networks Progress in Biomedical Optics and Imaging - Proceedings of Spie. 9041. DOI: 10.1117/12.2043872 |
0.782 |
|
| 2014 |
Litjens G, Huisman H, Elliott R, Shih N, Feldman M, Viswanath S, Fütterer J, Bomers J, Madabhushi A. Distinguishing benign confounding treatment changes from residual prostate cancer on MRI following laser ablation Progress in Biomedical Optics and Imaging - Proceedings of Spie. 9036. DOI: 10.1117/12.2043819 |
0.743 |
|
| 2014 |
Rusu M, Kurhanewicz J, Tewari A, Madabhushi A. A prostate MRI atlas of biochemical failures following cancer treatment Progress in Biomedical Optics and Imaging - Proceedings of Spie. 9035. DOI: 10.1117/12.2043775 |
0.444 |
|
| 2014 |
Singanamalli A, Wang H, Lee G, Shih N, Rosen M, Master S, Tomaszewski J, Feldman M, Madabhushi A. Supervised multi-view canonical correlation analysis: Fused multimodal prediction of disease diagnosis and prognosis Progress in Biomedical Optics and Imaging - Proceedings of Spie. 9038. DOI: 10.1117/12.2043762 |
0.483 |
|
| 2014 |
Litjens GJS, Elliott R, Shih N, Feldman M, Barentsz JO, Van De Kaa CAH, Kovacs I, Huisman HJ, Madabhushi A. Distinguishing prostate cancer from benign confounders via a cascaded classifier on multi-parametric MRI Progress in Biomedical Optics and Imaging - Proceedings of Spie. 9035. DOI: 10.1117/12.2043751 |
0.524 |
|
| 2014 |
Koundinyan S, Toth R, Madabhushi A, Maguire T. A statistical deformation model based regularizer for registration of histology and MRI Proceedings of the Ieee Annual Northeast Bioengineering Conference, Nebec. 2014. DOI: 10.1109/NEBEC.2014.6972845 |
0.301 |
|
| 2014 |
Tiwari P, Prasanna P, Rogers L, Wolansky L, Cohen M, Madabhushi A. NI-76 * COMPUTER EXTRACTED ORIENTED TEXTURE FEATURES ON T1-GADOLINIUM MRI FOR DISTINGUISHING RADIATION NECROSIS FROM RECURRENT BRAIN TUMORS Neuro-Oncology. 16: v155-v155. DOI: 10.1093/Neuonc/Nou264.74 |
0.587 |
|
| 2014 |
Tiwari P, Prasanna P, Jiang B, Barnholtz-Sloan J, Sloan A, Ostrom Q, Madabhushi A. NI-75 * QUANTITATIVE TEXTURE DESCRIPTORS ON BASELINE-MRI CAN PREDICT PATIENT SURVIVAL IN NEWLY DIAGNOSED GLIOBLASTOMA MULTIFORME PATIENTS Neuro-Oncology. 16: v155-v155. DOI: 10.1093/Neuonc/Nou264.73 |
0.568 |
|
| 2014 |
Prasanna P, Tiwari P, Madabhushi A. Co-occurrence of Local Anisotropic Gradient Orientations (CoLlAGe): Distinguishing tumor confounders and molecular subtypes on MRI Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 8675: 73-80. DOI: 10.1007/978-3-319-10443-0_10 |
0.584 |
|
| 2013 |
Tiwari P, Danish S, Wong S, Madabhushi A. Quantitative evaluation of multi-parametric MR imaging marker changes post-laser interstitial ablation therapy (LITT) for epilepsy. Proceedings of Spie--the International Society For Optical Engineering. 8671: 86711Y. PMID 25076822 DOI: 10.1117/12.2008157 |
0.602 |
|
| 2013 |
Viswanath S, Toth R, Rusu M, Sperling D, Lepor H, Futterer J, Madabhushi A. Quantitative Evaluation of Treatment Related Changes on Multi-Parametric MRI after Laser Interstitial Thermal Therapy of Prostate Cancer. Proceedings of Spie--the International Society For Optical Engineering. 8671: 86711F. PMID 24817802 DOI: 10.1117/12.2008037 |
0.732 |
|
| 2013 |
Cruz-Roa AA, Arevalo Ovalle JE, Madabhushi A, González Osorio FA. A deep learning architecture for image representation, visual interpretability and automated basal-cell carcinoma cancer detection. Medical Image Computing and Computer-Assisted Intervention : Miccai ... International Conference On Medical Image Computing and Computer-Assisted Intervention. 16: 403-10. PMID 24579166 DOI: 10.1007/978-3-642-40763-5_50 |
0.339 |
|
| 2013 |
Ginsburg S, Ali S, Lee G, Basavanhally A, Madabhushi A. Variable importance in nonlinear kernels (VINK): classification of digitized histopathology. Medical Image Computing and Computer-Assisted Intervention : Miccai ... International Conference On Medical Image Computing and Computer-Assisted Intervention. 16: 238-45. PMID 24579146 DOI: 10.1007/978-3-642-40763-5_30 |
0.768 |
|
| 2013 |
Lee G, Ali S, Veltri R, Epstein JI, Christudass C, Madabhushi A. Cell orientation entropy (COrE): predicting biochemical recurrence from prostate cancer tissue microarrays. Medical Image Computing and Computer-Assisted Intervention : Miccai ... International Conference On Medical Image Computing and Computer-Assisted Intervention. 16: 396-403. PMID 24505786 DOI: 10.1007/978-3-642-40760-4_50 |
0.361 |
|
| 2013 |
Rusu M, Bloch BN, Jaffe CC, Rofsky NM, Genega EM, Feleppa E, Lenkinski RE, Madabhushi A. Statistical 3D Prostate Imaging Atlas Construction via Anatomically Constrained Registration. Proceedings of Spie--the International Society For Optical Engineering. 8669. PMID 24392203 DOI: 10.1117/12.2006941 |
0.516 |
|
| 2013 |
Sparks R, Bloch BN, Feleppa E, Barratt D, Madabhushi A. Fully Automated Prostate Magnetic Resonance Imaging and Transrectal Ultrasound Fusion via a Probabilistic Registration Metric. Proceedings of Spie--the International Society For Optical Engineering. 8671. PMID 24353393 DOI: 10.1117/12.2007610 |
0.45 |
|
| 2013 |
Toth R, Ribault J, Gentile J, Sperling D, Madabhushi A. Simultaneous Segmentation of Prostatic Zones Using Active Appearance Models With Multiple Coupled Levelsets. Computer Vision and Image Understanding : Cviu. 117: 1051-1060. PMID 23997571 DOI: 10.1016/J.Cviu.2012.11.013 |
0.422 |
|
| 2013 |
Sparks R, Madabhushi A. Statistical Shape Model for Manifold Regularization: Gleason grading of prostate histology. Computer Vision and Image Understanding : Cviu. 117: 1138-1146. PMID 23888106 DOI: 10.1016/J.Cviu.2012.11.011 |
0.41 |
|
| 2013 |
Sparks R, Madabhushi A. Explicit shape descriptors: novel morphologic features for histopathology classification. Medical Image Analysis. 17: 997-1009. PMID 23850744 DOI: 10.1016/J.Media.2013.06.002 |
0.43 |
|
| 2013 |
Janowczyk A, Chandran S, Madabhushi A. Quantifying local heterogeneity via morphologic scale: Distinguishing tumoral from stromal regions. Journal of Pathology Informatics. 4: S8. PMID 23766944 DOI: 10.4103/2153-3539.109865 |
0.666 |
|
| 2013 |
Agner SC, Xu J, Madabhushi A. Spectral embedding based active contour (SEAC) for lesion segmentation on breast dynamic contrast enhanced magnetic resonance imaging. Medical Physics. 40: 032305. PMID 23464337 DOI: 10.1118/1.4790466 |
0.767 |
|
| 2013 |
Basavanhally A, Ganesan S, Feldman M, Shih N, Mies C, Tomaszewski J, Madabhushi A. Multi-field-of-view framework for distinguishing tumor grade in ER+ breast cancer from entire histopathology slides. Ieee Transactions On Bio-Medical Engineering. 60: 2089-99. PMID 23392336 DOI: 10.1109/Tbme.2013.2245129 |
0.794 |
|
| 2013 |
Tiwari P, Kurhanewicz J, Madabhushi A. Multi-kernel graph embedding for detection, Gleason grading of prostate cancer via MRI/MRS. Medical Image Analysis. 17: 219-35. PMID 23294985 DOI: 10.1016/J.Media.2012.10.004 |
0.673 |
|
| 2013 |
Ghaznavi F, Evans A, Madabhushi A, Feldman M. Digital imaging in pathology: whole-slide imaging and beyond. Annual Review of Pathology. 8: 331-59. PMID 23157334 DOI: 10.1146/Annurev-Pathol-011811-120902 |
0.425 |
|
| 2013 |
Madabhushi A, Doyle S, Basavanhally A, Gilmore H, Harris L, Shih N, Mies C, Feldman M, Tomaszewski J, Ganesan S. Abstract P4-03-04: Computer extracted image measurements of nuclear shape and texture from H&E images appear to stratify low and high risk ER+ breast cancers assessed via oncotype DX Cancer Research. 73. DOI: 10.1158/0008-5472.Sabcs13-P4-03-04 |
0.825 |
|
| 2013 |
Madabhushi A, Basavanhally A, Doyle S, Wan T, Singanamalli A, Thompson C, Gilmore H, Plecha D, Harris L. Abstract P2-03-01: Computer extracted image texture features on T2-weighted MRI appear to correlate with nuclear morphologic descriptors from H&E-stained histopathology in estrogen receptor positive breast cancers Cancer Research. 73. DOI: 10.1158/0008-5472.Sabcs13-P2-03-01 |
0.831 |
|
| 2013 |
Madabhushi A, Wan T, Bloch B, Plecha D, Thompson C, Gilmore H, Avril N, Jaffe C, Harris L. Abstract P2-02-12: Computer derived image features on DCE-MRI appear to distinguish estrogen receptor-positive breast cancers with low and high oncotype DX recurrence scores Cancer Research. 73. DOI: 10.1158/0008-5472.Sabcs13-P2-02-12 |
0.457 |
|
| 2013 |
Prabu SB, Toth R, Madabhushi A. A Statistical Deformation Model (SDM) based regularizer for non-rigid image registration: Application to registration of multimodal prostate MRI and histology Progress in Biomedical Optics and Imaging - Proceedings of Spie. 8676. DOI: 10.1117/12.2008707 |
0.448 |
|
| 2013 |
Ali S, Veltri R, Epstein JA, Christudass C, Madabhushi A. Cell cluster graph for prediction of biochemical recurrence in prostate cancer patients from tissue microarrays Progress in Biomedical Optics and Imaging - Proceedings of Spie. 8676. DOI: 10.1117/12.2008695 |
0.385 |
|
| 2013 |
Singanamalli A, Sparks R, Rusu M, Shih N, Ziober A, Tomaszewski J, Rosen M, Feldman M, Madabhushi A. Identifying in vivo DCE MRI parameters correlated with ex vivo quantitative microvessel architecture: A radiohistomorphometric approach Progress in Biomedical Optics and Imaging - Proceedings of Spie. 8676. DOI: 10.1117/12.2008136 |
0.515 |
|
| 2013 |
Ginsburg SB, Bloch BN, Rofsky NM, Genega EM, Lenkinski RE, Madabhushi A. Iterative multiple reference tissue method for estimating pharmacokinetic parameters on prostate DCE MRI Proceedings of Spie - the International Society For Optical Engineering. 8670. DOI: 10.1117/12.2007715 |
0.324 |
|
| 2013 |
Basavanhally A, Madabhushi A. Em-based segmentation-driven color standardization of digitized histopathology Progress in Biomedical Optics and Imaging - Proceedings of Spie. 8676. DOI: 10.1117/12.2007173 |
0.792 |
|
| 2013 |
Wan T, Nicolas Bloch B, Danish S, Madabhushi A. A novel point-based nonrigid image registration scheme based on learning optimal landmark configurations Progress in Biomedical Optics and Imaging - Proceedings of Spie. 8669. DOI: 10.1117/12.2007153 |
0.456 |
|
| 2013 |
Rusu M, Wang H, Golden T, Gow A, Madabhushi A. Multi-scale, multi-modal fusion of histological and MRI volumes for characterization of lung inammation Progress in Biomedical Optics and Imaging - Proceedings of Spie. 8672. DOI: 10.1117/12.2007148 |
0.406 |
|
| 2013 |
Wang H, Rusu M, Golden T, Gow A, Madabhushi A. Mouse lung volume reconstruction from efficient groupwise registration of individual histological slices with natural gradient@case.edu Progress in Biomedical Optics and Imaging - Proceedings of Spie. 8669. DOI: 10.1117/12.2006860 |
0.388 |
|
| 2013 |
Lee G, Sparks R, Ali S, Madabhushi A, Feldman MD, Master SR, Shih N, Tomaszewski JE. Co-occurring gland tensors in localized cluster graphs: Quantitative histomorphometry for predicting biochemical recurrence for intermediate grade prostate cancer Proceedings - International Symposium On Biomedical Imaging. 113-116. DOI: 10.1109/ISBI.2013.6556425 |
0.353 |
|
| 2013 |
Madabhushi A, Viswanath S, Lee G, Tiwari P. Medical Image Informatics for Personalized Medicine Critical Values. 6: 30-33. DOI: 10.1093/Criticalvalues/6.3.30 |
0.727 |
|
| 2012 |
Cruz-Roa A, González F, Galaro J, Judkins AR, Ellison D, Baccon J, Madabhushi A, Romero E. A visual latent semantic approach for automatic analysis and interpretation of anaplastic medulloblastoma virtual slides. Medical Image Computing and Computer-Assisted Intervention : Miccai ... International Conference On Medical Image Computing and Computer-Assisted Intervention. 15: 157-64. PMID 23285547 |
0.317 |
|
| 2012 |
Doyle S, Feldman MD, Shih N, Tomaszewski J, Madabhushi A. Cascaded discrimination of normal, abnormal, and confounder classes in histopathology: Gleason grading of prostate cancer. Bmc Bioinformatics. 13: 282. PMID 23110677 DOI: 10.1186/1471-2105-13-282 |
0.629 |
|
| 2012 |
Monaco JP, Madabhushi A. Class-specific weighting for Markov random field estimation: application to medical image segmentation. Medical Image Analysis. 16: 1477-89. PMID 22986078 DOI: 10.1016/J.Media.2012.06.007 |
0.337 |
|
| 2012 |
Toth R, Madabhushi A. Multifeature landmark-free active appearance models: application to prostate MRI segmentation. Ieee Transactions On Medical Imaging. 31: 1638-50. PMID 22665505 DOI: 10.1109/Tmi.2012.2201498 |
0.43 |
|
| 2012 |
Ali S, Madabhushi A. An integrated region-, boundary-, shape-based active contour for multiple object overlap resolution in histological imagery. Ieee Transactions On Medical Imaging. 31: 1448-60. PMID 22498689 DOI: 10.1109/Tmi.2012.2190089 |
0.403 |
|
| 2012 |
Chowdhury N, Toth R, Chappelow J, Kim S, Motwani S, Punekar S, Lin H, Both S, Vapiwala N, Hahn S, Madabhushi A. Concurrent segmentation of the prostate on MRI and CT via linked statistical shape models for radiotherapy planning. Medical Physics. 39: 2214-28. PMID 22482643 DOI: 10.1118/1.3696376 |
0.725 |
|
| 2012 |
Hipp J, Monaco J, Kunju LP, Cheng J, Yagi Y, Rodriguez-Canales J, Emmert-Buck MR, Hewitt S, Feldman MD, Tomaszewski JE, Toner M, Tompkins RG, Flotte T, Lucas D, Gilbertson JR, ... Madabhushi A, et al. Integration of architectural and cytologic driven image algorithms for prostate adenocarcinoma identification. Analytical Cellular Pathology (Amsterdam). 35: 251-65. PMID 22425661 DOI: 10.3233/Acp-2012-0054 |
0.445 |
|
| 2012 |
Viswanath SE, Bloch NB, Chappelow JC, Toth R, Rofsky NM, Genega EM, Lenkinski RE, Madabhushi A. Central gland and peripheral zone prostate tumors have significantly different quantitative imaging signatures on 3 Tesla endorectal, in vivo T2-weighted MR imagery. Journal of Magnetic Resonance Imaging : Jmri. 36: 213-24. PMID 22337003 DOI: 10.1002/Jmri.23618 |
0.817 |
|
| 2012 |
Viswanath S, Madabhushi A. Consensus embedding: theory, algorithms and application to segmentation and classification of biomedical data. Bmc Bioinformatics. 13: 26. PMID 22316103 DOI: 10.1186/1471-2105-13-26 |
0.671 |
|
| 2012 |
Bulman JC, Toth R, Patel AD, Bloch BN, McMahon CJ, Ngo L, Madabhushi A, Rofsky NM. Automated computer-derived prostate volumes from MR imaging data: comparison with radiologist-derived MR imaging and pathologic specimen volumes. Radiology. 262: 144-51. PMID 22190657 DOI: 10.1148/Radiol.11110266 |
0.461 |
|
| 2012 |
Janowczyk A, Chandran S, Singh R, Sasaroli D, Coukos G, Feldman MD, Madabhushi A. High-throughput biomarker segmentation on ovarian cancer tissue microarrays via hierarchical normalized cuts. Ieee Transactions On Bio-Medical Engineering. 59: 1240-52. PMID 22180503 DOI: 10.1109/Tbme.2011.2179546 |
0.724 |
|
| 2012 |
Cerutti S, Madabhushi A, Shah SK, Chon KH. Editorial: TBME Letters special section on multiscale biomedical signal and image modeling and analysis. Ieee Transactions On Bio-Medical Engineering. 59: 4-7. PMID 22180501 DOI: 10.1109/Tbme.2011.2178350 |
0.348 |
|
| 2012 |
Hipp J, Smith SC, Cheng J, Tomlins SA, Monaco J, Madabhushi A, Kunju LP, Balis UJ. Optimization of complex cancer morphology detection using the SIVQ pattern recognition algorithm. Analytical Cellular Pathology (Amsterdam). 35: 41-50. PMID 21988838 DOI: 10.3233/Acp-2011-0040 |
0.383 |
|
| 2012 |
Tiwari P, Viswanath S, Kurhanewicz J, Sridhar A, Madabhushi A. Multimodal wavelet embedding representation for data combination (MaWERiC): integrating magnetic resonance imaging and spectroscopy for prostate cancer detection. Nmr in Biomedicine. 25: 607-19. PMID 21960175 DOI: 10.1002/Nbm.1777 |
0.784 |
|
| 2012 |
Doyle S, Feldman M, Tomaszewski J, Madabhushi A. A boosted Bayesian multiresolution classifier for prostate cancer detection from digitized needle biopsies. Ieee Transactions On Bio-Medical Engineering. 59: 1205-18. PMID 20570758 DOI: 10.1109/Tbme.2010.2053540 |
0.695 |
|
| 2012 |
Veltri RW, Christudass C, Epstein JI, Ali S, Yoon H, Li C, Madabhushi A. Abstract 4061: Computer-assisted Gleason grading of prostate cancer: Two novel approaches using nuclear shape and texture feature to classify pathologic Gleason grade patterns 3 and 4 Cancer Research. 72: 4061-4061. DOI: 10.1158/1538-7445.Am2012-4061 |
0.483 |
|
| 2012 |
Toth R, Chappelow J, Vetter C, Kutter O, Russ C, Feldman M, Tomaszewski J, Shih N, Madabhushi A. Incorporating the whole-mount prostate histology reconstruction program Histostitcher© into the extensible imaging platform (XIP™) framework Progress in Biomedical Optics and Imaging - Proceedings of Spie. 8315. DOI: 10.1117/12.912938 |
0.755 |
|
| 2012 |
Sparks R, Madabhushi A. Gleason grading of prostate histology utilizing manifold regularization via statistical shape model of manifolds Progress in Biomedical Optics and Imaging - Proceedings of Spie. 8315. DOI: 10.1117/12.912887 |
0.405 |
|
| 2011 |
Tiwari P, Viswanath S, Lee G, Madabhushi A. MULTI-MODAL DATA FUSION SCHEMES FOR INTEGRATED CLASSIFICATION OF IMAGING AND NON-IMAGING BIOMEDICAL DATA. Proceedings / Ieee International Symposium On Biomedical Imaging: From Nano to Macro. Ieee International Symposium On Biomedical Imaging. 2011: 165-168. PMID 25705325 DOI: 10.1109/ISBI.2011.5872379 |
0.77 |
|
| 2011 |
Viswanath S, Tiwari P, Chappelow J, Toth R, Kurhanewicz J, Madabhushi A. CADOnc(©): An Integrated Toolkit For Evaluating Radiation Therapy Related Changes In The Prostate Using Multiparametric MRI. Proceedings / Ieee International Symposium On Biomedical Imaging: From Nano to Macro. Ieee International Symposium On Biomedical Imaging. 2011: 2095-2098. PMID 25360226 DOI: 10.1109/ISBI.2011.5872825 |
0.844 |
|
| 2011 |
Viswanath S, Bloch BN, Chappelow J, Patel P, Rofsky N, Lenkinski R, Genega E, Madabhushi A. Enhanced Multi-Protocol Analysis via Intelligent Supervised Embedding (EMPrAvISE): Detecting Prostate Cancer on Multi-Parametric MRI. Proceedings of Spie--the International Society For Optical Engineering. 7963: 79630U. PMID 25301991 DOI: 10.1117/12.878312 |
0.845 |
|
| 2011 |
Ali S, Madabhushi A. Graphical processing unit implementation of an integrated shape-based active contour: Application to digital pathology. Journal of Pathology Informatics. 2: S13. PMID 22811957 DOI: 10.4103/2153-3539.92029 |
0.425 |
|
| 2011 |
Basavanhally A, Feldman M, Shih N, Mies C, Tomaszewski J, Ganesan S, Madabhushi A. Multi-field-of-view strategy for image-based outcome prediction of multi-parametric estrogen receptor-positive breast cancer histopathology: Comparison to Oncotype DX. Journal of Pathology Informatics. 2: S1. PMID 22811953 DOI: 10.4103/2153-3539.92027 |
0.796 |
|
| 2011 |
Golugula A, Lee G, Master SR, Feldman MD, Tomaszewski JE, Madabhushi A. Supervised regularized canonical correlation analysis: integrating histologic and proteomic data for predicting biochemical failures. Conference Proceedings : ... Annual International Conference of the Ieee Engineering in Medicine and Biology Society. Ieee Engineering in Medicine and Biology Society. Annual Conference. 2011: 6434-7. PMID 22255811 DOI: 10.1109/IEMBS.2011.6091588 |
0.433 |
|
| 2011 |
Patel P, Chappelow J, Tomaszewski J, Feldman MD, Rosen M, Shih N, Madabhushi A. Spatially weighted mutual information (SWMI) for registration of digitally reconstructed ex vivo whole mount histology and in vivo prostate MRI. Conference Proceedings : ... Annual International Conference of the Ieee Engineering in Medicine and Biology Society. Ieee Engineering in Medicine and Biology Society. Annual Conference. 2011: 6269-72. PMID 22255771 DOI: 10.1109/IEMBS.2011.6091547 |
0.738 |
|
| 2011 |
Palumbo D, Yee B, O'Dea P, Leedy S, Viswanath S, Madabhushi A. Interplay between bias field correction, intensity standardization, and noise filtering for T2-weighted MRI. Conference Proceedings : ... Annual International Conference of the Ieee Engineering in Medicine and Biology Society. Ieee Engineering in Medicine and Biology Society. Annual Conference. 2011: 5080-3. PMID 22255481 DOI: 10.1109/IEMBS.2011.6091258 |
0.703 |
|
| 2011 |
Galaro J, Judkins AR, Ellison D, Baccon J, Madabhushi A. An integrated texton and bag of words classifier for identifying anaplastic medulloblastomas. Conference Proceedings : ... Annual International Conference of the Ieee Engineering in Medicine and Biology Society. Ieee Engineering in Medicine and Biology Society. Annual Conference. 2011: 3443-6. PMID 22255080 DOI: 10.1109/IEMBS.2011.6090931 |
0.356 |
|
| 2011 |
Hipp J, Cheng J, Pantanowitz L, Hewitt S, Yagi Y, Monaco J, Madabhushi A, Rodriguez-Canales J, Hanson J, Roy-Chowdhuri S, Filie AC, Feldman MD, Tomaszewski JE, Shih NN, Brodsky V, et al. Image microarrays (IMA): Digital pathology's missing tool. Journal of Pathology Informatics. 2: 47. PMID 22200030 DOI: 10.4103/2153-3539.86829 |
0.379 |
|
| 2011 |
Golugula A, Lee G, Master SR, Feldman MD, Tomaszewski JE, Speicher DW, Madabhushi A. Supervised regularized canonical correlation analysis: integrating histologic and proteomic measurements for predicting biochemical recurrence following prostate surgery. Bmc Bioinformatics. 12: 483. PMID 22182303 DOI: 10.1186/1471-2105-12-483 |
0.511 |
|
| 2011 |
Doyle S, Monaco J, Feldman M, Tomaszewski J, Madabhushi A. An active learning based classification strategy for the minority class problem: application to histopathology annotation. Bmc Bioinformatics. 12: 424. PMID 22034914 DOI: 10.1186/1471-2105-12-424 |
0.572 |
|
| 2011 |
Ali S, Veltri R, Epstein JI, Christudass C, Madabhushi A. Adaptive energy selective active contour with shape priors for nuclear segmentation and gleason grading of prostate cancer. Medical Image Computing and Computer-Assisted Intervention : Miccai ... International Conference On Medical Image Computing and Computer-Assisted Intervention. 14: 661-9. PMID 22003675 DOI: 10.1007/978-3-642-23623-5_83 |
0.359 |
|
| 2011 |
Cheng J, Hipp J, Monaco J, Lucas DR, Madabhushi A, Balis UJ. Automated vector selection of SIVQ and parallel computing integration MATLAB™: Innovations supporting large-scale and high-throughput image analysis studies. Journal of Pathology Informatics. 2: 37. PMID 21886893 DOI: 10.4103/2153-3539.83752 |
0.397 |
|
| 2011 |
Hipp JD, Sica J, McKenna B, Monaco J, Madabhushi A, Cheng J, Balis UJ. The need for the pathology community to sponsor a whole slide imaging repository with technical guidance from the pathology informatics community. Journal of Pathology Informatics. 2: 31. PMID 21845229 DOI: 10.4103/2153-3539.83191 |
0.311 |
|
| 2011 |
Chappelow J, Bloch BN, Rofsky N, Genega E, Lenkinski R, DeWolf W, Madabhushi A. Elastic registration of multimodal prostate MRI and histology via multiattribute combined mutual information. Medical Physics. 38: 2005-18. PMID 21626933 DOI: 10.1118/1.3560879 |
0.772 |
|
| 2011 |
Xu J, Janowczyk A, Chandran S, Madabhushi A. A high-throughput active contour scheme for segmentation of histopathological imagery. Medical Image Analysis. 15: 851-62. PMID 21570336 DOI: 10.1016/J.Media.2011.04.002 |
0.716 |
|
| 2011 |
Toth R, Bloch BN, Genega EM, Rofsky NM, Lenkinski RE, Rosen MA, Kalyanpur A, Pungavkar S, Madabhushi A. Accurate prostate volume estimation using multifeature active shape models on T2-weighted MRI. Academic Radiology. 18: 745-54. PMID 21549962 DOI: 10.1016/J.Acra.2011.01.016 |
0.382 |
|
| 2011 |
Chappelow J, Tomaszewski JE, Feldman M, Shih N, Madabhushi A. HistoStitcher(©): an interactive program for accurate and rapid reconstruction of digitized whole histological sections from tissue fragments. Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society. 35: 557-67. PMID 21397459 DOI: 10.1016/J.Compmedimag.2011.01.010 |
0.742 |
|
| 2011 |
Monaco JP, Madabhushi A. Weighted maximum posterior marginals for random fields using an ensemble of conditional densities from multiple Markov chain Monte Carlo simulations. Ieee Transactions On Medical Imaging. 30: 1353-64. PMID 21335309 DOI: 10.1109/Tmi.2011.2114896 |
0.314 |
|
| 2011 |
Madabhushi A, Agner S, Basavanhally A, Doyle S, Lee G. Computer-aided prognosis: predicting patient and disease outcome via quantitative fusion of multi-scale, multi-modal data. Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society. 35: 506-14. PMID 21333490 DOI: 10.1016/J.Compmedimag.2011.01.008 |
0.838 |
|
| 2011 |
Xiao G, Bloch BN, Chappelow J, Genega EM, Rofsky NM, Lenkinski RE, Tomaszewski J, Feldman MD, Rosen M, Madabhushi A. Determining histology-MRI slice correspondences for defining MRI-based disease signatures of prostate cancer. Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society. 35: 568-78. PMID 21255974 DOI: 10.1016/J.Compmedimag.2010.12.003 |
0.778 |
|
| 2011 |
Toth R, Tiwari P, Rosen M, Reed G, Kurhanewicz J, Kalyanpur A, Pungavkar S, Madabhushi A. A magnetic resonance spectroscopy driven initialization scheme for active shape model based prostate segmentation. Medical Image Analysis. 15: 214-25. PMID 21195016 DOI: 10.1016/J.Media.2010.09.002 |
0.646 |
|
| 2011 |
Agner SC, Soman S, Libfeld E, McDonald M, Thomas K, Englander S, Rosen MA, Chin D, Nosher J, Madabhushi A. Textural kinetics: A novel dynamic contrast-enhanced (DCE)-MRI feature for breast lesion classification Journal of Digital Imaging. 24: 446-463. PMID 20508965 DOI: 10.1007/S10278-010-9298-1 |
0.765 |
|
| 2011 |
Viswanath S, Palumbo D, Chappelow J, Patel P, Bloch BN, Rofsky N, Lenkinski R, Genega E, Madabhushi A. Empirical evaluation of bias field correction algorithms for computer-aided detection of prostate cancer on T2w MRI Progress in Biomedical Optics and Imaging - Proceedings of Spie. 7963. DOI: 10.1117/12.878813 |
0.822 |
|
| 2011 |
Sparks R, Madabhushi A. Content-based image retrieval utilizing explicit shape descriptors: Applications to breast MRI and prostate histopathology Progress in Biomedical Optics and Imaging - Proceedings of Spie. 7962. DOI: 10.1117/12.878428 |
0.52 |
|
| 2011 |
Ali S, Madabhushi A. Segmenting multiple overlapping objects via a hybrid active contour model incorporating shape priors: Applications to digital pathology Progress in Biomedical Optics and Imaging - Proceedings of Spie. 7962. DOI: 10.1117/12.878425 |
0.419 |
|
| 2011 |
Chowdhury N, Chappelow J, Toth R, Kim S, Hahn S, Vapiwala N, Lin H, Both S, Madabhushi A. Linked statistical shape models for multi-modal segmentation: Application to prostate CT-MR segmentation in radiotherapy planning Progress in Biomedical Optics and Imaging - Proceedings of Spie. 7963. DOI: 10.1117/12.878416 |
0.732 |
|
| 2011 |
Janowczyk A, Chandran S, Feldman M, Madabhushi A. Local morphologic scale: Application to segmenting tumor infiltrating lymphocytes in ovarian cancer TMAs Progress in Biomedical Optics and Imaging - Proceedings of Spie. 7962. DOI: 10.1117/12.878415 |
0.692 |
|
| 2011 |
Toth R, Bulman J, Patel AD, Bloch BN, Genega EM, Rofsky NM, Lenkinski RE, Madabhushi A. Integrating an adaptive region-based appearance model with a landmark-free statistical shape model: Application to prostate MRI segmentation Progress in Biomedical Optics and Imaging - Proceedings of Spie. 7962. DOI: 10.1117/12.878346 |
0.481 |
|
| 2011 |
Agner SC, Xu J, Rosen M, Karthigeyan S, Englander S, Madabhushi A. Spectral embedding based active contour (SEAC): Application to breast lesion segmentation on DCE-MRI Progress in Biomedical Optics and Imaging - Proceedings of Spie. 7963. DOI: 10.1117/12.878218 |
0.768 |
|
| 2011 |
Basavanhally A, Yu E, Xu J, Ganesan S, Feldman M, Tomaszewski J, Madabhushi A. Incorporating domain knowledge for tubule detection in breast histopathology using O'Callaghan neighborhoods Progress in Biomedical Optics and Imaging - Proceedings of Spie. 7963. DOI: 10.1117/12.878092 |
0.778 |
|
| 2011 |
Lai Y, Viswanath S, Baccon J, Ellison D, Judkins AR, Madabhushi A. A texture-based classifier to discriminate anaplastic from non-anaplastic medulloblastoma 2011 Ieee 37th Annual Northeast Bioengineering Conference, Nebec 2011. DOI: 10.1109/NEBC.2011.5778641 |
0.634 |
|
| 2011 |
Sridhar A, Doyle S, Madabhushi A. Boosted Spectral Embedding (BoSE): Applications to content-based image retrieval of histopathology Proceedings - International Symposium On Biomedical Imaging. 1897-1900. DOI: 10.1109/ISBI.2011.5872779 |
0.626 |
|
| 2011 |
Doyle S, Feldman M, Tomaszewski J, Shih N, Madabhushi A. Cascaded multi-class pairwise classifier (CascaMPa) for normal, cancerous, and cancer confounder classes in prostate histology Proceedings - International Symposium On Biomedical Imaging. 715-718. DOI: 10.1109/ISBI.2011.5872506 |
0.592 |
|
| 2011 |
Ali S, Madabhushi A. Active Contour for Overlap Resolution using Watershed BASED initialization (ACOReW): Applications to histopathology Proceedings - International Symposium On Biomedical Imaging. 614-617. DOI: 10.1109/ISBI.2011.5872482 |
0.352 |
|
| 2011 |
Basavanhally A, Ganesan S, Shih N, Mies C, Feldman M, Tomaszewski J, Madabhushi A. A boosted classifier for integrating multiple fields of view: Breast cancer grading in histopathology Proceedings - International Symposium On Biomedical Imaging. 125-128. DOI: 10.1109/ISBI.2011.5872370 |
0.791 |
|
| 2011 |
Tiwari P, Viswanath S, Kurhanewicz J, Madabhushi A. Weighted combination of multi-parametric MR imaging markers for evaluating radiation therapy related changes in the prostate Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 6963: 80-91. DOI: 10.1007/978-3-642-23944-1_9 |
0.773 |
|
| 2011 |
Ginsburg S, Tiwari P, Kurhanewicz J, Madabhushi A. Variable ranking with PCA: Finding multiparametric MR imaging markers for prostate cancer diagnosis and grading Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 6963: 146-157. DOI: 10.1007/978-3-642-23944-1_15 |
0.623 |
|
| 2010 |
Tiwari P, Kurhanewicz J, Rosen M, Madabhushi A. Semi supervised multi kernel (SeSMiK) graph embedding: identifying aggressive prostate cancer via magnetic resonance imaging and spectroscopy. Medical Image Computing and Computer-Assisted Intervention : Miccai ... International Conference On Medical Image Computing and Computer-Assisted Intervention. 13: 666-73. PMID 20879458 DOI: 10.1007/978-3-642-15711-0_83 |
0.628 |
|
| 2010 |
Sparks R, Madabhushi A. Novel morphometric based classification via diffeomorphic based shape representation using manifold learning. Medical Image Computing and Computer-Assisted Intervention : Miccai ... International Conference On Medical Image Computing and Computer-Assisted Intervention. 13: 658-65. PMID 20879457 DOI: 10.1007/978-3-642-15711-0_82 |
0.388 |
|
| 2010 |
Xu J, Monaco JP, Madabhushi A. Markov random field driven region-based active contour model (MaRACel): application to medical image segmentation. Medical Image Computing and Computer-Assisted Intervention : Miccai ... International Conference On Medical Image Computing and Computer-Assisted Intervention. 13: 197-204. PMID 20879400 DOI: 10.1007/978-3-642-15711-0_25 |
0.348 |
|
| 2010 |
Monaco JP, Tomaszewski JE, Feldman MD, Hagemann I, Moradi M, Mousavi P, Boag A, Davidson C, Abolmaesumi P, Madabhushi A. High-throughput detection of prostate cancer in histological sections using probabilistic pairwise Markov models. Medical Image Analysis. 14: 617-29. PMID 20493759 DOI: 10.1016/J.Media.2010.04.007 |
0.418 |
|
| 2010 |
Madabhushi A, Doyle S, Lee G, Basavanhally A, Monaco J, Masters S, Tomaszewski J, Feldman M. Integrated diagnostics: a conceptual framework with examples. Clinical Chemistry and Laboratory Medicine. 48: 989-98. PMID 20491597 DOI: 10.1515/Cclm.2010.193 |
0.828 |
|
| 2010 |
Fatakdawala H, Xu J, Basavanhally A, Bhanot G, Ganesan S, Feldman M, Tomaszewski JE, Madabhushi A. Expectation-maximization-driven geodesic active contour with overlap resolution (EMaGACOR): application to lymphocyte segmentation on breast cancer histopathology. Ieee Transactions On Bio-Medical Engineering. 57: 1676-89. PMID 20172780 DOI: 10.1109/Tbme.2010.2041232 |
0.797 |
|
| 2010 |
Juan D, Alexe G, Antes T, Liu H, Madabhushi A, Delisi C, Ganesan S, Bhanot G, Liou LS. Identification of a microRNA panel for clear-cell kidney cancer. Urology. 75: 835-41. PMID 20035975 DOI: 10.1016/J.Urology.2009.10.033 |
0.317 |
|
| 2010 |
Basavanhally AN, Ganesan S, Agner S, Monaco JP, Feldman MD, Tomaszewski JE, Bhanot G, Madabhushi A. Computerized image-based detection and grading of lymphocytic infiltration in HER2+ breast cancer histopathology. Ieee Transactions On Bio-Medical Engineering. 57: 642-53. PMID 19884074 DOI: 10.1109/Tbme.2009.2035305 |
0.832 |
|
| 2010 |
Xu J, Janowczyk A, Chandran S, Madabhushi A. A weighted mean shift, normalized cuts initialized color gradient based geodesic active contour model: Applications to histopathology image segmentation Progress in Biomedical Optics and Imaging - Proceedings of Spie. 7623. DOI: 10.1117/12.845602 |
0.707 |
|
| 2010 |
Xiao G, Bloch B, Chappelow J, Genega E, Rofsky N, Lenkinski R, Madabhushi A. A structural-functional MRI-based disease atlas: Application to computer-aided-diagnosis of prostate cancer Progress in Biomedical Optics and Imaging - Proceedings of Spie. 7623. DOI: 10.1117/12.845554 |
0.763 |
|
| 2010 |
Chappelow J, Both S, Viswanath S, Hahn S, Feldman MD, Rosen M, Tomaszewski J, Vapiwala N, Patel P, Madabhushi A. Computer-assisted targeted therapy (CATT) for prostate radiotherapy planning by fusion of CT and MRI Proceedings of Spie. 7625. DOI: 10.1117/12.844653 |
0.817 |
|
| 2010 |
Basavanhally A, Doyle S, Madabhushi A. Predicting classifier performance with a small training set: Applications to computer-aided diagnosis and prognosis 2010 7th Ieee International Symposium On Biomedical Imaging: From Nano to Macro, Isbi 2010 - Proceedings. 229-232. DOI: 10.1109/ISBI.2010.5490373 |
0.798 |
|
| 2010 |
Chappelow J, Madabhushi A. Multi-attribute combined mutual information (MACMI): An image registration framework for leveraging multiple data channels 2010 7th Ieee International Symposium On Biomedical Imaging: From Nano to Macro, Isbi 2010 - Proceedings. 376-379. DOI: 10.1109/ISBI.2010.5490330 |
0.75 |
|
| 2010 |
Madabhushi A, Basavanhally A, Doyle S, Agner S, Lee G. Computer-aided prognosis: Predicting patient and disease outcome via multi-modal image analysis 2010 7th Ieee International Symposium On Biomedical Imaging: From Nano to Macro, Isbi 2010 - Proceedings. 1415-1418. DOI: 10.1109/ISBI.2010.5490264 |
0.841 |
|
| 2010 |
Sparks R, Toth R, Chappelow J, Xiao G, Madabhushi A. An integrated framework for analyzing three-dimensional shape differences: Evaluating prostate morphometry 2010 7th Ieee International Symposium On Biomedical Imaging: From Nano to Macro, Isbi 2010 - Proceedings. 1081-1084. DOI: 10.1109/ISBI.2010.5490180 |
0.702 |
|
| 2010 |
Doyle S, Madabhushi A. Consensus of ambiguity: Theory and application of active learning for biomedical image analysis Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 6282: 313-324. DOI: 10.1007/978-3-642-16001-1_27 |
0.524 |
|
| 2010 |
Xu J, Sparks R, Janowcyzk A, Tomaszewski JE, Feldman MD, Madabhushi A. High-throughput prostate cancer gland detection, segmentation, and classification from digitized needle core biopsies Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 6367: 77-88. DOI: 10.1007/978-3-642-15989-3_10 |
0.432 |
|
| 2009 |
Viswanath S, Bloch BN, Rosen M, Chappelow J, Toth R, Rofsky N, Lenkinski R, Genega E, Kalyanpur A, Madabhushi A. Integrating Structural and Functional Imaging for Computer Assisted Detection of Prostate Cancer on Multi-Protocol In Vivo 3 Tesla MRI. Proceedings of Spie--the International Society For Optical Engineering. 7260: 72603I. PMID 25301989 DOI: 10.1117/12.811899 |
0.829 |
|
| 2009 |
Gurcan MN, Boucheron LE, Can A, Madabhushi A, Rajpoot NM, Yener B. Histopathological image analysis: a review. Ieee Reviews in Biomedical Engineering. 2: 147-71. PMID 20671804 DOI: 10.1109/Rbme.2009.2034865 |
0.416 |
|
| 2009 |
Tiwari P, Rosen M, Reed G, Kurhanewicz J, Madabhushi A. Spectral embedding based probabilistic boosting tree (ScEPTre): classifying high dimensional heterogeneous biomedical data. Medical Image Computing and Computer-Assisted Intervention : Miccai ... International Conference On Medical Image Computing and Computer-Assisted Intervention. 12: 844-51. PMID 20426190 DOI: 10.1007/978-3-642-04271-3_102 |
0.593 |
|
| 2009 |
Janowczyk A, Chandran S, Singh R, Sasaroli D, Coukos G, Feldman MD, Madabhushi A. Hierarchical normalized cuts: unsupervised segmentation of vascular biomarkers from ovarian cancer tissue microarrays. Medical Image Computing and Computer-Assisted Intervention : Miccai ... International Conference On Medical Image Computing and Computer-Assisted Intervention. 12: 230-8. PMID 20425992 DOI: 10.1007/978-3-642-04268-3_29 |
0.677 |
|
| 2009 |
Tiwari P, Rosen M, Madabhushi A. A hierarchical spectral clustering and nonlinear dimensionality reduction scheme for detection of prostate cancer from magnetic resonance spectroscopy (MRS). Medical Physics. 36: 3927-39. PMID 19810465 DOI: 10.1118/1.3180955 |
0.622 |
|
| 2009 |
Lexe G, Monaco J, Doyle S, Basavanhally A, Reddy A, Seiler M, Ganesan S, Bhanot G, Madabhushi A. Towards improved cancer diagnosis and prognosis using analysis of gene expression data and computer aided imaging. Experimental Biology and Medicine (Maywood, N.J.). 234: 860-79. PMID 19491367 DOI: 10.3181/0902-Mr-89 |
0.825 |
|
| 2009 |
Ganesan S, Madabhushi A, Basavanhally A, Xu J, Bhanot G, Barnard N, Toppmeyer D. Computerized Histologic Image-Based Risk Score (IbRiS) Classifier for ER+ Breast Cancer. Cancer Research. 69: 3046-3046. DOI: 10.1158/0008-5472.Sabcs-09-3046 |
0.798 |
|
| 2009 |
Naik J, Doyle S, Basavanally A, Ganesan S, Feldman MD, Tomaszewski JE, Madabhushi A. A boosted distance metric: Application to content based image retrieval and classification of digitized histopathology Progress in Biomedical Optics and Imaging - Proceedings of Spie. 7260. DOI: 10.1117/12.813931 |
0.675 |
|
| 2009 |
Toth R, Doyle S, Rosen M, Kalyanpur A, Pungavkar S, Bloch BN, Genega E, Rofsky N, Lenkinski R, Madabhushi A. WERITAS - Weighted ensemble of regional image textures for ASM segmentation Progress in Biomedical Optics and Imaging - Proceedings of Spie. 7259. DOI: 10.1117/12.812473 |
0.7 |
|
| 2009 |
Monaco J, Tomaszewski JE, Feldman MD, Moradi M, Mousavi P, Boag A, Davidson C, Abolmaesumi P, Madabhushi A. Probabilistic pairwise Markov models: application to prostate cancer detection Proceedings of Spie. 7259: 725903. DOI: 10.1117/12.812462 |
0.34 |
|
| 2009 |
Chappelow J, Bloch BN, Rofsky N, Genega E, Lenkinski R, Dewolf W, Viswanath S, Madabhushi A. COLLINARUS: Collection of image-derived non-linear attributes for registration using splines Progress in Biomedical Optics and Imaging - Proceedings of Spie. 7259. DOI: 10.1117/12.812352 |
0.846 |
|
| 2009 |
Agner SC, Xu J, Fatakdawala H, Ganesan S, Madabhushi A, Englander S, Rosen M, Thomas K, Schnall M, Feldman M, Tomaszewski J. Segmentation and classification of triple negative breast cancers using dce-mri Proceedings - 2009 Ieee International Symposium On Biomedical Imaging: From Nano to Macro, Isbi 2009. 1227-1230. DOI: 10.1109/ISBI.2009.5193283 |
0.737 |
|
| 2009 |
Basavanhally A, Xu J, Madabhushi A, Ganesan S. Computer-aided prognosis of er+ breast cancer histopathology and correlating survival outcomewith oncotype dx assay Proceedings - 2009 Ieee International Symposium On Biomedical Imaging: From Nano to Macro, Isbi 2009. 851-854. DOI: 10.1109/ISBI.2009.5193186 |
0.771 |
|
| 2009 |
Lee G, Doyle S, Monaco J, Madabhushi A, Feldman MD, Master SR, Tomaszewski JE. A knowledge representation framework for integration, classification of multi-scale imaging and non-imaging data: Preliminary results in predicting prostate cancer recurrence by fusing mass spectrometry and histology Proceedings - 2009 Ieee International Symposium On Biomedical Imaging: From Nano to Macro, Isbi 2009. 77-80. DOI: 10.1109/ISBI.2009.5192987 |
0.641 |
|
| 2008 |
Tiwari P, Rosen M, Madabhushi A. Consensus-locally linear embedding (C-LLE): application to prostate cancer detection on magnetic resonance spectroscopy. Medical Image Computing and Computer-Assisted Intervention : Miccai ... International Conference On Medical Image Computing and Computer-Assisted Intervention. 11: 330-8. PMID 18982622 DOI: 10.1007/978-3-540-85990-1-40 |
0.569 |
|
| 2008 |
Viswanath S, Bloch BN, Genega E, Rofsky N, Lenkinski R, Chappelow J, Toth R, Madabhushi A. A comprehensive segmentation, registration, and cancer detection scheme on 3 Tesla in vivo prostate DCE-MRI. Medical Image Computing and Computer-Assisted Intervention : Miccai ... International Conference On Medical Image Computing and Computer-Assisted Intervention. 11: 662-9. PMID 18979803 DOI: 10.1007/978-3-540-85988-8_79 |
0.817 |
|
| 2008 |
Toth R, Chappelow J, Rosen M, Pungavkar S, Kalyanpur A, Madabhushi A. Multi-attribute non-initializing texture reconstruction based active shape model (MANTRA). Medical Image Computing and Computer-Assisted Intervention : Miccai ... International Conference On Medical Image Computing and Computer-Assisted Intervention. 11: 653-61. PMID 18979802 DOI: 10.1007/978-3-540-85988-8_78 |
0.757 |
|
| 2008 |
Lee G, Rodriguez C, Madabhushi A. Investigating the efficacy of nonlinear dimensionality reduction schemes in classifying gene and protein expression studies. Ieee/Acm Transactions On Computational Biology and Bioinformatics / Ieee, Acm. 5: 368-84. PMID 18670041 DOI: 10.1109/Tcbb.2008.36 |
0.331 |
|
| 2008 |
Souza A, Udupa JK, Madabhushi A. Image filtering via generalized scale. Medical Image Analysis. 12: 87-98. PMID 17827051 DOI: 10.1016/J.Media.2007.07.007 |
0.337 |
|
| 2008 |
Viswanath S, Tiwari P, Rosen M, Madabhushi A. A meta-classifier for detecting prostate cancer by quantitative integration of in vivo magnetic resonance spectroscopy and magnetic resonance imaging Progress in Biomedical Optics and Imaging - Proceedings of Spie. 6915. DOI: 10.1117/12.771022 |
0.784 |
|
| 2008 |
Agner SC, Soman S, Libfeld E, McDonald M, Rosen MA, Schnall MD, Chin D, Nosher J, Madabhushi A. Novel kinetic texture features for breast lesion classification on dynamic contrast enhanced (DCE) MRI Progress in Biomedical Optics and Imaging - Proceedings of Spie. 6915. DOI: 10.1117/12.770920 |
0.736 |
|
| 2008 |
Viswanath S, Rosen M, Madabhushi A. A consensus embedding approach for segmentation of high resolution in vivo prostate magnetic resonance imagery Progress in Biomedical Optics and Imaging - Proceedings of Spie. 6915. DOI: 10.1117/12.770868 |
0.728 |
|
| 2008 |
Toth R, Tiwari P, Rosen M, Kalyanpur A, Pungavkar S, Madabhushi A. A multi-modal prostate segmentation scheme by combining spectral clustering and active shape models Progress in Biomedical Optics and Imaging - Proceedings of Spie. 6914. DOI: 10.1117/12.770772 |
0.584 |
|
| 2008 |
Chappelow J, Viswanath S, Monaco J, Rosen M, Tomaszewski J, Feldman M, Madabhushi A. Improving supervised classification accuracy using non-rigid multimodal image registration: Detecting prostate cancer Progress in Biomedical Optics and Imaging - Proceedings of Spie. 6915. DOI: 10.1117/12.770703 |
0.84 |
|
| 2008 |
Doyle S, Agner S, Madabhushi A, Feldman M, Tomaszewski J. Automated grading of breast cancer histopathology using spectral clustering with textural and architectural image features 2008 5th Ieee International Symposium On Biomedical Imaging: From Nano to Macro, Proceedings, Isbi. 496-499. DOI: 10.1109/ISBI.2008.4541041 |
0.818 |
|
| 2008 |
Naik S, Doyle S, Agner S, Madabhushi A, Feldman M, Tomaszewski J. Automated gland and nuclei segmentation for grading of prostate and breast cancer histopathology 2008 5th Ieee International Symposium On Biomedical Imaging: From Nano to Macro, Proceedings, Isbi. 284-287. DOI: 10.1109/ISBI.2008.4540988 |
0.815 |
|
| 2007 |
Tiwari P, Madabhushi A, Rosen M. A hierarchical unsupervised spectral clustering scheme for detection of prostate cancer from magnetic resonance spectroscopy (MRS). Medical Image Computing and Computer-Assisted Intervention : Miccai ... International Conference On Medical Image Computing and Computer-Assisted Intervention. 10: 278-86. PMID 18044579 |
0.578 |
|
| 2007 |
Chappelow J, Madabhushi A, Rosen M, Tomaszeweski J, Feldman M. Multimodal image registration of ex vivo 4 Tesla MRI with whole mount histology for prostate cancer detection Progress in Biomedical Optics and Imaging - Proceedings of Spie. 6512. DOI: 10.1117/12.710558 |
0.764 |
|
| 2007 |
Naik S, Madabhushi A, Tomaszeweski J, Feldman MD. A quantitative exploration of efficacy of gland morphology in prostate cancer grading Bioengineering, Proceedings of the Northeast Conference. 58-59. DOI: 10.1109/NEBC.2007.4413278 |
0.386 |
|
| 2007 |
Doyle S, Hwang M, Shah K, Madabhushi A, Feldman M, Tomaszeweski J. Automated grading of prostate cancer using architectural and textural image features 2007 4th Ieee International Symposium On Biomedical Imaging: From Nano to Macro - Proceedings. 1284-1287. DOI: 10.1109/ISBI.2007.357094 |
0.635 |
|
| 2007 |
Chappelow J, Madabhushi A, Rosen M, Tomaszeweski J, Feldman M. A combined feature ensemble based mutual information scheme for robust inter-modal, inter-protocol image registration 2007 4th Ieee International Symposium On Biomedical Imaging: From Nano to Macro - Proceedings. 644-647. DOI: 10.1109/ISBI.2007.356934 |
0.746 |
|
| 2006 |
Doyle S, Rodriguez C, Madabhushi A, Tomaszeweski J, Feldman M. Detecting prostatic adenocarcinoma from digitized histology using a multi-scale hierarchical classification approach. Conference Proceedings : ... Annual International Conference of the Ieee Engineering in Medicine and Biology Society. Ieee Engineering in Medicine and Biology Society. Annual Conference. 1: 4759-62. PMID 17947116 DOI: 10.1109/IEMBS.2006.260188 |
0.613 |
|
| 2006 |
Madabhushi A, Yang P, Rosen M, Weinstein S. Distinguishing lesions from posterior acoustic shadowing in breast ultrasound via non-linear dimensionality reduction. Conference Proceedings : ... Annual International Conference of the Ieee Engineering in Medicine and Biology Society. Ieee Engineering in Medicine and Biology Society. Annual Conference. 1: 3070-3. PMID 17947006 DOI: 10.1109/IEMBS.2006.260189 |
0.312 |
|
| 2006 |
Doyle S, Madabhushi A, Feldman M, Tomaszeweski J. A boosting cascade for automated detection of prostate cancer from digitized histology. Medical Image Computing and Computer-Assisted Intervention : Miccai ... International Conference On Medical Image Computing and Computer-Assisted Intervention. 9: 504-11. PMID 17354810 |
0.652 |
|
| 2006 |
Madabhushi A, Udupa JK. New methods of MR image intensity standardization via generalized scale. Medical Physics. 33: 3426-34. PMID 17022239 DOI: 10.1118/1.2335487 |
0.453 |
|
| 2006 |
Madabhushi A, Udupa JK, Moonis G. Comparing MR image intensity standardization against tissue characterizability of magnetization transfer ratio imaging. Journal of Magnetic Resonance Imaging : Jmri. 24: 667-75. PMID 16878312 DOI: 10.1002/Jmri.20658 |
0.408 |
|
| 2006 |
Madabhushi A, Udupa JK, Souza A. Generalized scale: Theory, algorithms, and application to image inhomogeneity correction Computer Vision and Image Understanding. 101: 100-121. DOI: 10.1016/J.Cviu.2005.07.010 |
0.302 |
|
| 2006 |
Madabhushi A, Shi J, Feldman M, Rosen M, Tomaszewski J. Comparing ensembles of learners: Detecting prostate cancer from high resolution MRI Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 4241: 25-36. |
0.361 |
|
| 2005 |
Madabhushi A, Feldman MD, Metaxas DN, Tomaszeweski J, Chute D. Automated detection of prostatic adenocarcinoma from high-resolution ex vivo MRI. Ieee Transactions On Medical Imaging. 24: 1611-25. PMID 16350920 DOI: 10.1109/Tmi.2005.859208 |
0.519 |
|
| 2005 |
Madabhushi A, Udupa JK. Interplay between intensity standardization and inhomogeneity correction in MR image processing. Ieee Transactions On Medical Imaging. 24: 561-76. PMID 15889544 DOI: 10.1109/Tmi.2004.843256 |
0.43 |
|
| 2003 |
Madabhushi A, Metaxas DN. Combining low-, high-level and empirical domain knowledge for automated segmentation of ultrasonic breast lesions. Ieee Transactions On Medical Imaging. 22: 155-69. PMID 12715992 DOI: 10.1109/Tmi.2002.808364 |
0.428 |
|
| 2003 |
Madabhushi A, Feldman M, Metaxas D, Chute D, Tomaszeweski J. Optimal Feature Combination for Automated Segmentation of Prostatic Adenocarcinoma from High Resolution MRI Annual International Conference of the Ieee Engineering in Medicine and Biology - Proceedings. 1: 614-617. |
0.395 |
|
| 2003 |
Madabhushi A, Feldman M, Metaxas D, Chute D, Tomaszewski J. A novel stochastic combination of 3D texture features for automated segmentation of prostatic adenocarcinoma from high resolution MRI Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2878: 581-591. |
0.343 |
|
| 2002 |
Madabhushi A, Udupa JK. Evaluating intensity standardization and inhomogeneity correction in magnetic resonance images Bioengineering, Proceedings of the Northeast Conference. 137-138. DOI: 10.1109/NEBC.2002.999503 |
0.323 |
|
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