  Mask R-CNN is a state-of-the-art network architecture for the detection and
segmentation of object instances in the computer vision domain. In this
contribution, it is used to localize, label and segment individual ribs in
anterior-posterior chest X-ray images. For this purpose, several extensions
have been made to the original architecture, in order to address the specific
challenges of this application. This includes the use of rib specific networks,
facilitating dedicated anchor boxes sampled from a training set, as well as a
sequential processing of all ribs. Here, the segmentation result of the upper
neighbor rib is used as additional input to the network. This approach is the
first addressing both rib segmentation and anatomical labeling in chest
radiographs. The results are comparable or even better than existing methods
aiming only at segmentation.
