Deep-learning-based Segmentation of Fundus Photographs to Detect Central Serous Chorioretinopathy
Version 1https://doi.org/10.1167/tvst.11.2.22 Simple Code Implementation for Deep Learning–Based Segmentation to Evaluate Central Serous Chorioretinopathy in Fundus Photography, TVST, 2022 We developed a pix2pix deep learning model for segmentation of subretinal fluid area in fundus photographs to detect central serous chorioretinopathy (CSC). The total dataset included fundus photographs and a segmentation image dataset from 194 eyes with CSC from the medical centers and publicly accessible datasets.
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https://doi.org/10.1167/tvst.11.2.22 Simple Code Implementation for Deep Learning–Based Segmentation to Evaluate Central Serous Chorioretinopathy in Fundus Photography, TVST, 2022
We developed a pix2pix deep learning model for segmentation of subretinal fluid area in fundus photographs to detect central serous chorioretinopathy (CSC).
The total dataset included fundus photographs and a segmentation image dataset from 194 eyes with CSC from the medical centers and publicly accessible datasets.