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ORCIDRakesh Shiradkar
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2020 – today
- 2024
[j4]Amogh Hiremath
, Vidya Sankar Viswanathan, Kaustav Bera, Rakesh Shiradkar, Lei Yuan, Keith Armitage, Robert Gilkeson, Mengyao Ji, Pingfu Fu, Amit Gupta, Cheng Lu, Anant Madabhushi:
Deep learning reveals lung shape differences on baseline chest CT between mild and severe COVID-19: A multi-site retrospective study. Comput. Biol. Medicine 177: 108643 (2024)- [j3]Babajide O. Owosela, Rebecca S. Steinberg, Sharon L. Leslie, Leo A. Celi, Saptarshi Purkayastha, Rakesh Shiradkar, Janice M. Newsome, Judy W. Gichoya:
Identifying and improving the "ground truth" of race in disparities research through improved EMR data reporting. A systematic review. Int. J. Medical Informatics 182: 105303 (2024) - 2023
- [j2]Davide Chicco, Rakesh Shiradkar:
Ten quick tips for computational analysis of medical images. PLoS Comput. Biol. 19(1) (2023) - 2022
- [c8]Ansh Roge, Amogh Hiremath, Michael Sobota, Sree Harsha Tirumani, Leonardo Kayat Bittencourt, Justin Ream, Ryan Ward, Halimat Olaniyan, Sadhna Verma, Andrei S. Purysko, Anant Madabhushi, Rakesh Shiradkar:
Evaluating the sensitivity of deep learning to inter-reader variations in lesion delineations on bi-parametric MRI in identifying clinically significant prostate cancer. Computer-Aided Diagnosis 2022 - 2021
- [c7]Amogh Hiremath, Lei Yuan, Rakesh Shiradkar, Kaustav Bera, Vidya Sankar Viswanathan, Pranjal Vaidya, Jennifer Furin, Keith Armitage, Robert Gilkeson, Mengyao Ji, Pingfu Fu, Amit Gupta, Cheng Lu, Anant Madabhushi:
LuMiRa: An Integrated Lung Deformation Atlas and 3D-CNN Model of Infiltrates for COVID-19 Prognosis. MICCAI (7) 2021: 367-377 - 2020
- [c6]Amogh Hiremath, Rakesh Shiradkar, Nathaniel Braman, Prateek Prasanna, Ardeshir R. Rastinehad, Andrei S. Purysko, Anant Madabhushi:
A combination of intra- and peri-tumoral deep features from prostate bi-parametric MRI can distinguish clinically significant and insignificant prostate cancer. Computer-Aided Diagnosis 2020 - [c5]Rakesh Shiradkar, Ruyuan Zuo, Amr Mahran, Lee Ponsky, Sree Harsha Tirumani, Anant Madabhushi:
Radiomic features derived from periprostatic fat on pre-surgical T2w MRI predict extraprostatic extension of prostate cancer identified on post-surgical pathology: preliminary results. Computer-Aided Diagnosis 2020
2010 – 2019
- 2019
- [c4]Lin Li, Rakesh Shiradkar, Ahmad Algohary, Patrick Leo, Cristina Magi-Galluzzi, Eric Klein, Andrei S. Purysko, Anant Madabhushi:
Radiomic features derived from pre-operative multi-parametric MRI of prostate cancer are associated with Decipher risk score. Computer-Aided Diagnosis 2019: 109503Y - 2017
- [c3]Soumya Ghose, Rakesh Shiradkar, Mirabela Rusu, Jhimli Mitra, Rajat Thawani, Michael D. Feldman, Amar Gupta, Andrei S. Purysko, Lee Ponsky, Anant Madabhushi:
Field Effect Induced Organ Distension (FOrge) Features Predicting Biochemical Recurrence from Pre-treatment Prostate MRI. MICCAI (2) 2017: 442-449 - 2014
- [j1]Rakesh Shiradkar, Ping Tan, Sim Heng Ong:
Auto-calibrating photometric stereo using ring light constraints. Mach. Vis. Appl. 25(3): 801-809 (2014) - [c2]Rakesh Shiradkar, Li Shen, George V. Landon, Sim Heng Ong, Ping Tan:
A New Perspective on Material Classification and Ink Identification. CVPR 2014: 2275-2282 - 2013
- [c1]Rakesh Shiradkar, Sim Heng Ong:
Surface reconstruction using isocontours of constant depth and gradient. ICIP 2013: 360-363
Coauthor Index
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last updated on 2024-11-28 21:27 CET by the dblp team
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