4 papers
Training-inference input alignment outweighs framework choice in longitudinal retinal image prediction
Liyin Chen, Nazlee Zebardast, Mengyu Wang +2
Predicting disease progression from longitudinal imaging is useful for clinical decision making and trial design. Recent methods have moved toward increasing generative complexity,…
CataractSAM-2: A Domain-Adapted Model for Anterior Segment Surgery Segmentation and Scalable Ground-Truth Annotation
Mohammad Eslami, Dhanvinkumar Ganeshkumar, Saber Kazeminasab +8
We present CataractSAM-2, a domain-adapted extension of Meta's Segment Anything Model 2, designed for real-time semantic segmentation of cataract ophthalmic surgery videos with hig…
EVLF-FM: Explainable Vision Language Foundation Model for Medicine
Yang Bai, Haoran Cheng, Yang Zhou +40
Despite the promise of foundation models in medical AI, current systems remain limited - they are modality-specific and lack transparent reasoning processes, hindering clinical ado…
Multimodal, Multi-Disease Medical Imaging Foundation Model (MerMED-FM)
Yang Zhou, Chrystie Wan Ning Quek, Jun Zhou +22
Current artificial intelligence models for medical imaging are predominantly single modality and single disease. Attempts to create multimodal and multi-disease models have resulte…