4 citations · 8 across the 4 of their papers we have counts for
4 papers
DRAC: Diabetic Retinopathy Analysis Challenge with Ultra-Wide Optical Coherence Tomography Angiography Images
Bo Qian, Hao Chen, Xiangning Wang +18
Computer-assisted automatic analysis of diabetic retinopathy (DR) is of great importance in reducing the risks of vision loss and even blindness. Ultra-wide optical coherence tomog…
Key Feature Replacement of In-Distribution Samples for Out-of-Distribution Detection
Jaeyoung Kim, Seo Taek Kong, Dongbin Na +1
Out-of-distribution (OOD) detection can be used in deep learning-based applications to reject outlier samples from being unreliably classified by deep neural networks. Learning to…
Bag of Tricks for Developing Diabetic Retinopathy Analysis Framework to Overcome Data Scarcity
Gitaek Kwon, Eunjin Kim, Sunho Kim +3
Recently, diabetic retinopathy (DR) screening utilizing ultra-wide optical coherence tomography angiography (UW-OCTA) has been used in clinical practices to detect signs of early D…
AI-based automated Meibomian gland segmentation, classification and reflection correction in infrared Meibography
Ripon Kumar Saha, A. M. Mahmud Chowdhury, Kyung-Sun Na +6
Purpose: Develop a deep learning-based automated method to segment meibomian glands (MG) and eyelids, quantitatively analyze the MG area and MG ratio, estimate the meiboscore, and…