5 papers
Representation Transfer of Foundation Models for Ultra-Widefield Retinal Imaging
Mingya Alexa Gong, Da Ma, Lovre Antonio Budimir +7
Despite the widespread adoption of foundation models as feature extractors for medical imaging, relatively little is understood about how different pretraining strategies influence…
PC-Seg: Progressive Cross-View Consistency for 3D OCT Segmentation from Sparse 2D Annotations
Tsubasa Konno, Takahiro Ninomiya, Yukun Zhou +6
Volumetric segmentation of optical coherence tomography (OCT) images is essential for diagnosing ocular diseases but requires labor-intensive voxel-wise annotations. While semi-sup…
oculomix: Hierarchical Sampling for Retinal-Based Systemic Disease Prediction
Hyunmin Kim, Yukun Zhou, Rahul A. Jonas +4
Oculomics - the concept of predicting systemic diseases, such as cardiovascular disease and dementia, through retinal imaging - has advanced rapidly due to the data efficiency of t…
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.…
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…