Vertebrae detection and localization in CT with two-stage CNNs and dense annotations

We propose a new, two-stage approach to the vertebrae cen-troid detection and localization problem. The first stage detects wherethe vertebrae appear in the scan using 3D samples, the second identifiesthe specific vertebrae within that region-of-interest using 2D slices. Oursolution utilizes new techniques to improve the accuracy of the algorithmsuch as a revised approach to dense labelling from sparse centroid anno-tations and usage of large anisotropic kernels in the base level of a U-netarchitecture to maximize the receptive field. Our method improves thestate-of-the-art’s mean localization accuracy by 0.87mm on a publiclyavailable spine CT benchmark