Fig. 2.

Overview of the deep learning pipeline. T2-weighted axial slices are passed into V-Net segmentation models to obtain masks for the intervertebral disc and dural sac. Geometric rules based on the disc and dural sac are used to localize bounding boxes around foramen and facet. Each localized region is passed into its corresponding classifier: Big Transfer (BiT) convolutional neural network (CNN) for classification of lumbar spinal stenosis, foraminal stenosis, and facet arthropathy. Interpretable classification (decision tree) of lumbar spinal stenosis relies on additional quantitative metrics extracted from the disc and dural sac segmentations