Deep Learning based spine labeling with three-plane 2D localizers without vertebrae segmentation

In this work , we describe a deep learning-based methodology to generate vertebrae labels directly from the standard 2D tri-planar localizer images without the need any additional scanning or explicitly segmenting the vertebrae. This is accomplished by using deep-learning setup a to identify vertebrae labels directly on the localizer images. The method is demonstrated on lumbar spine localizer data to identify Thoracic-12 (T12), Lumbar-4 (L4) , and Sacral-1 (S1) vertebrae locations. In a test cohort of 50 lumbar MR spine exams, we report labeling accuracy of 92%, 98% and 96% for T12, L4 and S1 vertebrae respectively on localizer images.