1. A Deep Learning Approach to Digitally Stain Optical Coherence Tomography Images of the Optic Nerve Head

    A Deep Learning Approach to Digitally Stain Optical Coherence Tomography Images of the Optic Nerve Head

    Purpose. To develop a deep learning approach to digitally-stain optical coherence tomography (OCT) images of the optic nerve head (ONH). Methods. A horizontal B-scan was acquired through the center of the ONH using OCT (Spectralis) for 1 eye of each of 100 subjects (40 normal & 60 glaucoma). All images were enhanced using adaptive compensation. A custom deep learning network was then designed and trained with the compensated images to digitally stain (i.e. highlight) 6 tissue layers of the ONH. The accuracy of our algorithm was assessed (against manual segmentations) using the Dice coefficient, sensitivity, and specificity. We further studied ...

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