DEEP LEARNING FOR OPTICAL COHERENCE TOMOGRAPHY SEGMENTATION
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United States of America Patent
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Issued Date -
Apr 20, 2023
app pub date -
Dec 20, 2022
filing date -
Dec 20, 2022
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Abstract
Systems and methods are presented for providing a machine learning model for segmenting an optical coherence tomography (OCT) image. A first OCT image is obtained, and then labeled with identified boundaries associated with different tissues in the first OCT image using a graph search algorithm. Portions of the labeled first OCT image are extracted to generate a first plurality of image tiles. A second plurality of image tiles is generated by manipulating at least one image tile from the first plurality of image tiles, such as by rotating and/or flipping the at least one image tile. The machine learning model is trained using the first plurality of image tiles and the second plurality of image tiles. The trained machine learning model is used to perform segmentation in a second OCT image.
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