论文标题
目标挑战的数据集和评估算法设计
Dataset and Evaluation algorithm design for GOALS Challenge
论文作者
论文摘要
青光眼会导致视力神经损害导致不可逆转的视力丧失，并且无法治愈青光眼。OCT成像方式是评估青光眼损害的重要技术，因为它有助于量化底底结构。为了促进对青光眼的OCT辅助诊断领域中对AI技术的研究，我们与国际医学图像计算和计算机辅助干预（MICCAI）2022的国际医学图像会议（MICCAI）进行了青光眼OCT分析和层细分（目标）挑战，以提供来自Oct Image sections for Oct Image sectionation的数据和记录，从而从Glaucmom和Glaucmoma中进行研究。本文介绍了已发布的300个Circumpapillary OCT图像，两个子任务的基线以及评估方法。目标挑战可在https://aistudio.baidu.com/aistudio/competition/detail/230访问。
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.
