Anant Madabhushi

Biomedical Engineering Rutgers University, New Brunswick, New Brunswick, NJ, United States 
Biomedical Engineering, Pathology, Oncology
"Anant Madabhushi"
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Koyuncu C, Janowczyk A, Farre X, et al. (2023) 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
Li L, Shiradkar R, Gottlieb N, et al. (2023) Multi-scale statistical deformation based co-registration of prostate MRI and post-surgical whole mount histopathology. Medical Physics
Corredor G, Bharadwaj S, Pathak T, et al. (2023) A Review of AI-Based Radiomics and Computational Pathology Approaches in Triple-Negative Breast Cancer: Current Applications and Perspectives. Clinical Breast Cancer
Serafin R, Koyuncu C, Xie W, et al. (2023) Nondestructive 3D pathology with analysis of nuclear features for prostate cancer risk assessment. The Journal of Pathology
Chen Y, Li H, Janowczyk A, et al. (2023) Computational pathology improves risk stratification of a multi-gene assay for early stage ER+ breast cancer. Npj Breast Cancer. 9: 40
Chen Y, Zee J, Janowczyk AR, et al. (2023) Clinical Relevance of Computationally Derived Attributes of Peritubular Capillaries from Kidney Biopsies. Kidney360
Iyer S, Ismail M, Tamrazi B, et al. (2022) 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
Zhou Y, Koyuncu C, Lu C, et al. (2022) Multi-site cross-organ calibrated deep learning (MuSClD): Automated diagnosis of non-melanoma skin cancer. Medical Image Analysis. 84: 102702
Alilou M, Khorrami M, Prasanna P, et al. (2022) A tumor vasculature-based imaging biomarker for predicting response and survival in patients with lung cancer treated with checkpoint inhibitors. Science Advances. 8: eabq4609
Whitney J, Dollinger L, Tamrazi B, et al. (2022) Quantitative Nuclear Histomorphometry Predicts Molecular Subtype and Clinical Outcome in Medulloblastomas: Preliminary Findings. Journal of Pathology Informatics. 13: 100090
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