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arXiv · 2207.14447

Dataset and Evaluation algorithm design for GOALS Challenge

Huihui Fang·Fei Li·Huazhu Fu·Junde Wu·Xiulan Zhang·Yanwu Xu
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Abstract

Glaucoma causes irreversible vision loss due to damage to the optic nerve, and there is no cure for glaucoma.OCT imaging modality is an essential technique for assessing glaucomatous damage since it aids in quantifying fundus structures. To promote the research of AI technology in the field of OCT-assisted diagnosis of glaucoma, we held a Glaucoma OCT Analysis and Layer Segmentation (GOALS) Challenge in conjunction with the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2022 to provide data and corresponding annotations for researchers studying layer segmentation from OCT images and the classification of glaucoma. This paper describes the released 300 circumpapillary OCT images, the baselines of the two sub-tasks, and the evaluation methodology. The GOALS Challenge is accessible at https://aistudio.baidu.com/aistudio/competition/detail/230.

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Huihui Fang, Fei Li, Huazhu Fu, Junde Wu, Xiulan Zhang, Yanwu Xu. 2022-07-29. Dataset and Evaluation algorithm design for GOALS Challenge. https://arxiv.org/abs/2207.14447

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