Researchers have introduced Cataract-LMM, a large-scale benchmark dataset designed to advance deep learning in surgical video analysis. This dataset comprises 3,000 cataract surgery videos from two centers, featuring diverse annotations including surgical phases, instrument segmentation, and skill assessment metrics. The benchmark aims to facilitate the development of more generalizable multi-task models for analyzing surgical workflows and improving training. AI
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IMPACT Enables development of more generalizable multi-task models for surgical workflow analysis and competency-based training.
RANK_REASON The cluster contains an academic paper introducing a new benchmark dataset for deep learning in surgical video analysis.