Peripheral nerve fascicle tracing and longitudinal analysis of the damaging effects of electrical overstimulation using novel polarization sensitive optical coherence tomography (PS-OCT) based biomarkers currently require manual image segmentation to determine the boundaries of the nerve tissue within the acquired OCT volume. We developed an algorithm for automated peripheral nerve tissue classification based on image segmentation of the multimodal swept-source PS-OCT volumes. We compare the performance of density-based and neural network-based classifiers, and demonstrate results on fixed nerve tissues as well as on in vivo acquired data from a rat sciatic nerve and mini-pig vagus nerve.
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