1. Intermediate and Deep Capillary Plexuses in Machine Learning Segmentation of High-Resolution Optical Coherence Tomography Imaging

    Intermediate and Deep Capillary Plexuses in Machine Learning Segmentation of High-Resolution Optical Coherence Tomography Imaging

    Purpose: To describe imaging produced by machine learning based segmentation of high-resolution optical coherence tomography (OCT) imaging of the intermediate capillary plexus (ICP) and deep capillary plexus (DCP), layers of vessels not imaged well by dye-based angiography. Methods: Three healthy subjects with no ocular problems were imaged with spectral domain OCT using an instrument with a scanning speed of 85,000 A-scans per second and 3µm axial optical resolution. A random forest segmentation strategy was used to segment the ICP and DCP. The depth resolved imaging data was visualized with the help of volume rendering. Results: The high-resolution OCT ...

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