| Year |
Citation |
Score |
| 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, ... ... Tiwari P, 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 |
0.491 |
|
| 2022 |
Tiwari P, Pant B, Elarabawy MM, Abd-Elnaby M, Mohd N, Dhiman G, Sharma S. CNN Based Multiclass Brain Tumor Detection Using Medical Imaging. Computational Intelligence and Neuroscience. 2022: 1830010. PMID 35774437 DOI: 10.1155/2022/1830010 |
0.342 |
|
| 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 |
0.483 |
|
| 2022 |
Antunes J, Ismail M, Hossain I, Wang Z, Prasanna P, Madabushi A, Tiwari P, Viswanath S. RADIomic Spatial TexturAl descripTor (RADISTAT): Quantifying spatial organization of imaging heterogeneity associated with tumor response to treatment. Ieee Journal of Biomedical and Health Informatics. PMID 35085099 DOI: 10.1109/JBHI.2022.3146778 |
0.689 |
|
| 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 |
0.721 |
|
| 2020 |
Beig N, Bera K, Tiwari P. Introduction to radiomics and radiogenomics in neuro-oncology: implications and challenges. Neuro-Oncology Advances. 2: iv3-iv14. PMID 33521636 DOI: 10.1093/noajnl/vdaa148 |
0.351 |
|
| 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 |
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 |
0.54 |
|
| 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 |
0.767 |
|
| 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 |
0.484 |
|
| 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, ... Tiwari P, 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 |
0.546 |
|
| 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 |
0.6 |
|
| 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 |
0.536 |
|
| 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 |
0.504 |
|
| 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 |
0.537 |
|
| 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 |
0.503 |
|
| 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, et al. Perinodular and Intranodular Radiomic Features on Lung CT Images Distinguish Adenocarcinomas from Granulomas. Radiology. 180910. PMID 30561278 DOI: 10.1148/Radiol.2018180910 |
0.527 |
|
| 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 |
0.577 |
|
| 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, 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 |
0.743 |
|
| 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 |
0.599 |
|
| 2018 |
Rogers L, Tatsuoka C, Machtay M, Badve C, Tiwari P, Prasanna P, Sloan A, Selman W, Cohen M. NCMP-01. COMPARISON AND QUANTITATION OF HISTOPATHOLOGY ABNORMALITIES IN SURGICALLY RESECTED CEREBRAL RADIATION NECROSIS AS COMPARED WITH RECURRENT BRAIN TUMOR FOLLOWING RADIATION Neuro-Oncology. 20: vi194-vi194. DOI: 10.1093/Neuonc/Noy148.803 |
0.326 |
|
| 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 |
0.484 |
|
| 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 |
0.511 |
|
| 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 |
0.507 |
|
| 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 |
0.491 |
|
| 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 |
0.505 |
|
| 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 |
0.55 |
|
| 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 |
0.702 |
|
| 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 |
0.601 |
|
| 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 |
0.563 |
|
| 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 |
0.451 |
|
| 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 |
0.498 |
|
| 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 |
0.564 |
|
| 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 |
0.604 |
|
| 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 |
0.554 |
|
| 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 |
0.598 |
|
| 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 |
0.555 |
|
| 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 |
0.532 |
|
| 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 |
0.483 |
|
| 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 |
0.51 |
|
| 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 |
0.587 |
|
| 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 |
0.576 |
|
| 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 |
0.6 |
|
| 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 |
0.565 |
|
| 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 |
0.516 |
|
| 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 |
0.592 |
|
| 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 |
0.585 |
|
| 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 |
0.542 |
|
| 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 |
0.516 |
|
| 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 |
0.577 |
|
| 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 |
0.623 |
|
| 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 |
0.676 |
|
| 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 |
0.749 |
|
| 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 |
0.716 |
|
| 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 |
0.798 |
|
| 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 |
0.579 |
|
| 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 |
0.743 |
|
| 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 |
0.56 |
|
| 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 |
0.566 |
|
| 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 |
0.535 |
|
| 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 |
0.565 |
|
| 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 |
0.485 |
|
| 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 |
0.744 |
|
| 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 |
0.502 |
|
| 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 |
0.491 |
|
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