activity
20222025
most citedGeneralist versus Specialist Vision Foundation Models for Ocular Disease and Oculomics

2 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

eess.IV2025★ 2 cited

Generalist versus Specialist Vision Foundation Models for Ocular Disease and Oculomics

Yukun Zhou, Paul Nderitu, Jocelyn Hui Lin Goh +20

Medical foundation models, pre-trained with large-scale clinical data, demonstrate strong performance in diverse clinically relevant applications. RETFound, trained on nearly one m…

cs.CV2025

FusionFM: Fusing Eye-specific Foundational Models for Optimized Ophthalmic Diagnosis

Ke Zou, Jocelyn Hui Lin Goh, Yukun Zhou +11

Foundation models (FMs) have shown great promise in medical image analysis by improving generalization across diverse downstream tasks. In ophthalmology, several FMs have recently…

eess.IV2025

Is an Ultra Large Natural Image-Based Foundation Model Superior to a Retina-Specific Model for Detecting Ocular and Systemic Diseases?

Qingshan Hou, Yukun Zhou, Jocelyn Hui Lin Goh +19

The advent of foundation models (FMs) is transforming medical domain. In ophthalmology, RETFound, a retina-specific FM pre-trained sequentially on 1.4 million natural images and 1.…

eess.IV2024

Enhancing Community Vision Screening -- AI Driven Retinal Photography for Early Disease Detection and Patient Trust

Xiaofeng Lei, Yih-Chung Tham, Jocelyn Hui Lin Goh +7

Community vision screening plays a crucial role in identifying individuals with vision loss and preventing avoidable blindness, particularly in rural communities where access to ey…

eess.IV2022

Localizing Anatomical Landmarks in Ocular Images using Zoom-In Attentive Networks

Xiaofeng Lei, Shaohua Li, Xinxing Xu +9

Localizing anatomical landmarks are important tasks in medical image analysis. However, the landmarks to be localized often lack prominent visual features. Their locations are elus…