Spine detection in CT and MR using iterated marginal space learning

► We present a learning-based approach that works on CT and MR alike. ► A novel iterative extension of marginal space learning is proposed. ► A novel probabilistic prior on spinal disk position, orientation and scale is used. ► An adaptive segmentation approach, robust towards pathologies and degenerations. ► Competitive detection rates, accuracy and computational speed are achieved.