Any reporting on an MR spine scans involves labeling of the vertebrae. Hence, providing labeled spine images for reading can save significant time for radiologists. First step of an automated labeling is reliable segmentation of vertebral bodies. Most of the studies provide methods only for the segmentation and labeling of only a part of the spine. Here, we have used a variant of U-Net based Deep Learning architecture for segmenting vertebrae of Whole Spine. The network was trained with 165 datasets of whole spine images and tested with 8 datasets. We achieved average DICE score of 0.921.
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