Retinal Vessel Plexus Differentiation Based on OCT Angiography Using Deep Learning

Abstract

Listen

Translate article

PurposeWhile structural optical coherence tomography (OCT) is traditionally used to differentiate the vascular plexus layers in OCT angiography (OCTA), the vascular plexuses do not always obey the retinal laminations. We sought to segment the superficial, deep and avascular plexuses from OCTA images using deep learning without structural OCT image input or segmentation boundaries. DesignCross-sectional study. SubjectsThe study included 235 OCTA cubes from 33 patients for training and testing of the model. MethodsFrom each OCTA cube, 3 weakly labeled images representing the superficial, deep and avascular plexuses were obtained for a total of 705 starting images. Images were augmented with standard intensity and geometric transforms, and regions from adjacent plexuses were programmatically combined to create synthetic 2-class images for each OCTA cube. Images were partitioned on a per patient basis into training, validation, and reserved test groups to train and evaluate a U-Net based machine learning model. To investigate the generalization of the model we applied the model to multi-class thin slabs from OCTA volumes and qualitatively observed the resulting b-scans. Main Outcome MeasuresPlexus segmentation performance was assessed quantitatively using Dice scores on a held-out test set. ResultsAfter training on single class plexus images, our model achieved good results (Dice scores > .82) and was further improved when using the synthetic 2-class images (Dice > .95). While not trained on more complex multi-class slabs, the model performed plexus labeling on slab data that indicates the use of only OCTA data shows promise for segmenting the superficial, deep and avascular plexuses without requiring OCT layer segmentations, and the use of synthetic 2-class images makes a significant performance improvement. ConclusionsThis study presents the use of OCTA data alone to segment the superficial, deep and avascular plexuses of the retina, confirming that use of structural OCT layer segmentations as boundaries is not required.