Rakesh Shiradkar

8PUBLICATIONS
17CO-AUTHORS
Deep learningMedical physicsPredictive and prognostic markersPhotogrammetry and remote sensing
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Publications (8)

|Aug 26, 2026
Enhancing Robustness of Deep Learning to Batch Effects from Multi-site Data for Segmentation of Clinically Significant Prostate Cancer on MRI.

|Aug 26, 2025
Population-Specific Radiomics From Biparametric Magnetic Resonance Imaging Improves Prostate Cancer Risk Stratification in African American Men.

Abhishek Midya, Sreeharsha Tirumani, Leonardo Kayat Bittencourt

|May 04, 2021
Computer extracted gland features from H&E predicts prostate cancer recurrence comparably to a genomic companion diagnostic test: a large multi-site study.

Patrick Leo, Andrew Janowczyk, Robin Elliott

|Sep 03, 2020
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.

Rakesh Shiradkar, Ananya Panda, Patrick Leo

|May 08, 2018
Radiomic features from pretreatment biparametric MRI predict prostate cancer biochemical recurrence: Preliminary findings.

Rakesh Shiradkar, Soumya Ghose, Ivan Jambor

|Nov 11, 2016
Radiomics based targeted radiotherapy planning (Rad-TRaP): a computational framework for prostate cancer treatment planning with MRI.

Rakesh Shiradkar, Tarun K Podder, Ahmad Algohary

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Frequent Collaborators

2 joint publications

Pingfu Fu

2 joint publications

Anant Madabhushi

1 joint publications

Andrei S Purysko

1 joint publications

Patrick Leo