Sunny Virmani
Sunny Virmani
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Predicting the risk of developing diabetic retinopathy using deep learning
A Bora, S Balasubramanian, B Babenko, S Virmani, S Venugopalan, ...
The Lancet Digital Health 3 (1), e10-e19, 2021
Fundus photograph-based deep learning algorithms in detecting diabetic retinopathy
R Raman, S Srinivasan, S Virmani, S Sivaprasad, C Rao, R Rajalakshmi
Eye 33 (1), 97-109, 2019
Towards generalist biomedical ai
T Tu, S Azizi, D Driess, M Schaekermann, M Amin, PC Chang, A Carroll, ...
NEJM AI 1 (3), AIoa2300138, 2024
Real-time diabetic retinopathy screening by deep learning in a multisite national screening programme: a prospective interventional cohort study
P Ruamviboonsuk, R Tiwari, R Sayres, V Nganthavee, K Hemarat, ...
The Lancet Digital Health 4 (4), e235-e244, 2022
Dynamic perfusion CT assessment of the blood-brain barrier permeability: first pass versus delayed acquisition
JW Dankbaar, J Hom, T Schneider, SC Cheng, BC Lau, I Van Der Schaaf, ...
American Journal of Neuroradiology 29 (9), 1671-1676, 2008
Dynamic ablation device
EE Greenblatt, KI Trovato, TJ Naypauer, S Virmani
US Patent App. 13/516,757, 2012
Age-and anatomy-related values of blood-brain barrier permeability measured by perfusion-CT in non-stroke patients
JW Dankbaar, J Hom, T Schneider, SC Cheng, BC Lau, I van der Schaaf, ...
Journal of neuroradiology 36 (4), 219-227, 2009
Lessons learned from translating AI from development to deployment in healthcare
K Widner, S Virmani, J Krause, J Nayar, R Tiwari, ER Pedersen, D Jeji, ...
Nature Medicine 29 (6), 1304-1306, 2023
Fully automated segmentation of carotid and vertebral arteries from contrast-enhanced CTA
O Cuisenaire, S Virmani, ME Olszewski, R Ardon
Medical Imaging 2008: Image Processing 6914, 1210-1217, 2008
Electronic colon-cleansing for CT colonography: diagnostic performance
MS Juchems, A Ernst, P Johnson, S Virmani, HJ Brambs, AJ Aschoff
Abdominal imaging 34, 359-364, 2009
Accuracy and anatomical coverage of perfusion CT assessment of the blood-brain barrier permeability: one bolus versus two boluses
JW Dankbaar, J Hom, T Schneider, SC Cheng, BC Lau, I Van Der Schaaf, ...
Cerebrovascular Diseases 26 (6), 600-605, 2008
Dynamic acquisition sampling rate for computed tomography perfusion (CTP) imaging
M Vembar, TB Ivanc, S Virmani
US Patent 9,955,934, 2018
Fundus imaging apparatus
EH Iliffe-Moon, TR Swiss, MR Toh, KD Wood, CT Wing, S Virmani, ...
US Patent App. 29/602,209, 2019
Towards Generalist Biomedical AI.(2023)
T Tu, S Azizi, D Driess, M Schaekermann, M Amin, PC Chang, A Carroll, ...
URL https://arxiv. org/abs/2307.14334, 2023
Performance of a diabetic retinopathy deep learning model for ultra-widefield imaging
T Peto, LP Aiello, SR Sadda, D Lewis, AM Cairns, D Keane, S Virmani, ...
Investigative Ophthalmology & Visual Science 63 (7), 587–A0152-587–A0152, 2022
Automatic polyp detection and measurement with computed tomographic colonography: A phantom study
S Virmani, AS Lev-Toaff, LM Ciancibello
Biomedical Imaging and Intervention Journal 5 (3), 2009
S Virmani
US Patent 9,020,578, 2015
Single scan multi-procedure imaging
S Virmani, TJ Naypauer, DB McKnight
US Patent 8,594,406, 2013
Deep learning for predicting the progression of diabetic retinopathy using fundus images
A Bora, B Babenko, S Virmani, J Cuadros, S Balasubramanian, ...
Investigative Ophthalmology & Visual Science 61 (7), 1639-1639, 2020
Wide field imaging of the retina using a new slit scan ophthalmoscope (SSO) imager
KS Kunert, K Taeubig, M Blum, S Saur, K O'Hara, MK Durbin, B Daniel, ...
Investigative Ophthalmology & Visual Science 57 (12), 1677-1677, 2016
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