arXiv:2110.10965

2020 CATARACTS Semantic Segmentation Challenge

Imanol Luengo, Maria Grammatikopoulou, Rahim Mohammadi, Chris Walsh, Chinedu Innocent Nwoye, Deepak Alapatt, Nicolas Padoy, Zhen-Liang Ni, Chen-Chen Fan, Gui-Bin Bian, Zeng-Guang Hou, Heonjin Ha, Jiacheng Wang, Haojie Wang, Dong Guo 외 25명

제출 2021-10-21

원문 초록

Surgical scene segmentation is essential for anatomy and instrument localization which can be further used to assess tissue-instrument interactions during a surgical procedure. In 2017, the Challenge on Automatic Tool Annotation for cataRACT Surgery (CATARACTS) released 50 cataract surgery videos accompanied by instrument usage annotations. These annotations included frame-level instrument presence information. In 2020, we released pixel-wise semantic annotations for anatomy and instruments for 4670 images sampled from 25 videos of the CATARACTS training set. The 2020 CATARACTS Semantic Segmentation Challenge, which was a sub-challenge of the 2020 MICCAI Endoscopic Vision (EndoVis) Challenge, presented three sub-tasks to assess participating solutions on anatomical structure and instrument segmentation. Their performance was assessed on a hidden test set of 531 images from 10 videos of the CATARACTS test set.

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