activity
20182025
most citedPredicting Risk of Developing Diabetic Retinopathy using Deep Learning

251 citations · 389 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2025

APTOS-2024 challenge report: Generation of synthetic 3D OCT images from fundus photographs

Bowen Liu, Weiyi Zhang, Peranut Chotcomwongse +23

Optical Coherence Tomography (OCT) provides high-resolution, 3D, and non-invasive visualization of retinal layers in vivo, serving as a critical tool for lesion localization and di…

eess.IV2025

Predicting Diabetic Macular Edema Treatment Responses Using OCT: Dataset and Methods of APTOS Competition

Weiyi Zhang, Peranut Chotcomwongse, Yinwen Li +15

Diabetic macular edema (DME) significantly contributes to visual impairment in diabetic patients. Treatment responses to intravitreal therapies vary, highlighting the need for pati…

eess.IV2020★ 251 cited

Predicting Risk of Developing Diabetic Retinopathy using Deep Learning

Ashish Bora, Siva Balasubramanian, Boris Babenko +13

Diabetic retinopathy (DR) screening is instrumental in preventing blindness, but faces a scaling challenge as the number of diabetic patients rises. Risk stratification for the dev…

cs.CV2020

Scientific Discovery by Generating Counterfactuals using Image Translation

Arunachalam Narayanaswamy, Subhashini Venugopalan, Dale R. Webster +10

Model explanation techniques play a critical role in understanding the source of a model's performance and making its decisions transparent. Here we investigate if explanation tech…

cs.CV2018★ 138 cited

Predicting optical coherence tomography-derived diabetic macular edema grades from fundus photographs using deep learning

Avinash Varadarajan, Pinal Bavishi, Paisan Raumviboonsuk +15

Diabetic eye disease is one of the fastest growing causes of preventable blindness. With the advent of anti-VEGF (vascular endothelial growth factor) therapies, it has become incre…