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ABSTRACT: Purpose
To evaluate choroidal vasculature using a novel three-dimensional algorithm in fellow eyes of patients with unilateral chronic central serous chorioretinopathy (cCSC).Methods
Patients with unilateral cCSC were retrospectively included. Automated choroidal segmentation was conducted using a deep-learning ResUNet model. Phansalkar thresholding was applied to binarize choroidal vasculature, and three-dimensional maps were created. Mean choroidal vessel diameter, intervessel distance, choroidal thickness, and choroidal vascularity index (CVI) were measured. Linear mixed models were used for statistical analysis.Results
Thirty unilateral cCSC eyes, 22 fellow, and 26 controls were included. Both cCSC and fellow eyes exhibited significant higher mean choroidal vess
SUBMITTER: Valsecchi N
PROVIDER: S-EPMC12422394 | biostudies-literature | 2025 Sep
REPOSITORIES: biostudies-literature