Open-source deep learning-based automatic segmentation of mouse Schlemm's canal in optical coherence tomography images
Abstract
The purpose of this study was to develop an automatic deep learning-based approach and corresponding free, open-source software to perform segmentation of the Schlemm's canal (SC) lumen in optical coherence tomography (OCT) scans of living mouse eyes. A novel convolutional neural network (CNN) for semantic segmentation grounded in a U-Net architecture was developed by incorporating a late fusion scheme, multi-scale input image pyramid, dilated...
Paper Details
Title
Open-source deep learning-based automatic segmentation of mouse Schlemm's canal in optical coherence tomography images
Published Date
Jan 1, 2022
Journal
Volume
214
Pages
108844 - 108844
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