OIMHS: An Optical Coherence Tomography Image Dataset Based on Macular Hole Manual Segmentation.

ABSTRACT: Macular holes, one of the most common macular diseases, require timely treatment. The morphological changes on optical coherence tomography (OCT) images provided an opportunity for direct observation of the disease, and accurate segmentation was needed to identify and quantify the lesions. Developments of such algorithms had been obstructed by a lack of high-quality datasets (the OCT images and the corresponding gold standard macular hole segmentation labels), especially for supervised learning-based segmentation algorithms. In such context, we established a large OCT image macular hole segmentation (OIMHS) dataset with 3859 B-scan images of 119 patients, and each image provided four segmentation labels: retina, macular hole, intraretinal cysts, and choroid. This dataset offered an excelle

SUBMITTER: Ye X 

PROVIDER: S-EPMC10628143 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature