52 citations · 87 across the 5 of their papers we have counts for
5 papers
Gradient based Severity Labeling for Biomarker Classification in OCT
Kiran Kokilepersaud, Mohit Prabhushankar, Ghassan AlRegib +2
In this paper, we propose a novel selection strategy for contrastive learning for medical images. On natural images, contrastive learning uses augmentations to select positive and…
Clinically Labeled Contrastive Learning for OCT Biomarker Classification
Kiran Kokilepersaud, Stephanie Trejo Corona, Mohit Prabhushankar +2
This paper presents a novel positive and negative set selection strategy for contrastive learning of medical images based on labels that can be extracted from clinical data. In the…
OLIVES Dataset: Ophthalmic Labels for Investigating Visual Eye Semantics
Mohit Prabhushankar, Kiran Kokilepersaud, Yash-yee Logan +3
Clinical diagnosis of the eye is performed over multifarious data modalities including scalar clinical labels, vectorized biomarkers, two-dimensional fundus images, and three-dimen…
Multi-Modal Learning Using Physicians Diagnostics for Optical Coherence Tomography Classification
Y. Logan, K. Kokilepersaud, G. Kwon +3
In this paper, we propose a framework that incorporates experts diagnostics and insights into the analysis of Optical Coherence Tomography (OCT) using multi-modal learning. To demo…
A Novel Deep Learning Pipeline for Retinal Vessel Detection in Fluorescein Angiography
Li Ding, Mohammad H. Bawany, Ajay E. Kuriyan +3
While recent advances in deep learning have significantly advanced the state of the art for vessel detection in color fundus (CF) images, the success for detecting vessels in fluor…