In this study, we propose to combine miniaturized optical coherence tomography (OCT) catheter with a residual neural network (ResNet)-based deep learning model for differentiation of normal from cancerous colorectal tissue in fresh ex vivo specimens. The OCT catheter has an outer diameter of 3.8 mm, a lateral resolution of ~10 um, and an axial resolution of 6 um. A customized ResNet-based neural network structure was trained on both benchtop and catheter images. An AUC of 0.97 was achieved to distinguish between normal and cancerous colorectal tissue when testing on the rest of catheter images.
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