1. Automated segmentation of en face choroidal images obtained by optical coherent tomography by machine learning

    Automated segmentation of en face choroidal images obtained by optical coherent tomography by machine learning

    Purpose To develop an automated method to segment the choroidal layers of en face optical coherent tomography (OCT) images by machine learning. Study design A cross-sectional, prospective study of 276 eyes of 181 healthy subjects. Methods OCT en face images of the choroid were obtained every 2.6 μm from the retinal pigment epithelium (RPE) to the chorioscleral border. The images at the start of the choriocapillaris, start of Sattler’s layer, and start of Haller’s layer were identified, and the image numbers from the RPE line were taken as the teacher data. Forty-one feature quantities of each image ...

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