Differentiating Choroidal Melanomas and Nevi Using a Self-Supervised Deep Learning Model Applied to Clinical Fundoscopy Images

Differentiating Choroidal Melanomas and Nevi Using a Self-Supervised Deep Learning Model Applied to Clinical Fundoscopy Images

Purpose: Testing the validity of a self-supervised deep learning (DL) model, RETFound, for use on posterior uveal (choroidal) melanoma (UM) and nevus differentiation. Design: Case-control study. Subjects: Ultrawidefield fundoscopy images, both color and autofluorescence, were used for this study, ob...

Full description

Saved in:
Bibliographic Details
Main Authors: Max Jackson, MPhys, Helen Kalirai, BSc, PhD, Rumana N. Hussain, MBBS, MD, Heinrich Heimann, MD, PhD, Yalin Zheng, MEng, PhD, Sarah E. Coupland, MBBS, PhD
Format: Article
Language:English
Published: Elsevier 2025-03-01
Series:Ophthalmology Science
Subjects:
Choroidal melanoma
Deep learning
Foundation models
Fundoscopy
Nevi
Online Access:http://www.sciencedirect.com/science/article/pii/S2666914524001830
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

http://www.sciencedirect.com/science/article/pii/S2666914524001830

Similar Items