Scientific data · 2026
Multicenter fine annotated surgical video dataset for minimally invasive glaucoma surgery.
СтатьяDatasetНазвание и аннотация: Перевод пока не подготовлен
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Wang Deming, Zhang Yinhang, Li Yirui, Zhou Kai, Yang Zefeng, You Zeng, Xiaokaiti Dilimulati, Zhou Fengqi, Chen Yu, Li Xiaoyan, Yan Xiaowei, Xu Guihua, Wang Zhixuan, Jiang Jiaxuan, Xie Lin, Zhu Xiaomin, Jin Ling, Wang Zhenyu, Han Ying, Tang Guangxian, Fan Sujie, Li Fei, Tan Mingkui, Zhang Xiulan
Аннотация
Minimally invasive glaucoma surgery (MIGS) presents substantial challenges due to its intricate procedures and high technical demands, necessitating robust surgical navigation systems. The development of these systems is highly dependent on the availability of precisely annotated datasets. Addressing this need, we have created the first multicenter, large-scale, fine-annotated surgical video dataset for MIGS. This dataset includes millions of frames, extensively annotated with both surgical instruments and anatomical structures. The annotations are organized into two primary tasks: Task I, which involves phase recognition to identify different stages of the surgery, and Task II, which focuses on semantic segmentation of surgical instruments and anatomical details. By providing a foundational resource for training computer vision models, our dataset aims to facilitate the development of advanced computer-assisted interventions that can improve the precision and safety of glaucoma surgeries.