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International audience; Kidney segmentation in 3D CT images allows extracting useful information for nephrologists. For practical use in clinical routine, such an algorithm should be fast, automatic and robust to contrast-agent enhancement and elds of view. By combining and re ning state-of-the-art techniques (random forests and template deformation), we demonstrate the possibility of building an algorithm that meets these requirements. Kidneys are localized with random forests following a coarse to fi ne strategy. Their initial positions detected with global contextual information are re ned with a cascade of local regression forests. A classi cation forest is then used to obtain a probabilistic segmentation of both kidneys. The nal segmentation is performed with an implicit template deformation algorithm driven by these kidney probability maps. Our method has been validated on a highly heterogeneous database of 233 CT scans from 89 patients. 80 % of the kidneys were accurately detected and segmented (Dice coe cient > 0:90) in a few seconds per volume. Copyright Springer-Verlag Berlin Heidelberg 2012. The original publication is available at www.springerlink.com: http://link.springer.com/chapter/10.1007%2F978-3-642-33454-2_9

We propose a recursive Bayesian model for the delineation of coronary arteries from 3D CT angiograms (cardiac CTA) and discuss the use of discrete minimal path techniques as an efficient optimization scheme for the propagation of model realizations on a discrete graph. Design issues such as the definition of a suitable accumulative metric are analyzed in the context of our probabilistic formulation. Our approach jointly optimizes the vascular centerline and associated radius on a 4D space+scale graph. It employs a simple heuristic scheme to dynamically limit scale-space exploration for increased computational performance. It incorporates prior knowledge on radius variations and derives the local data likelihood from a multiscale, oriented gradient flux-based feature. From minimal cost path techniques, it inherits practical properties such as computational efficiency and workflow versatility. We quantitatively evaluated a two-point interactive implementation on a large and varied cardiac CTA database. Additionally, results from the Rotterdam Coronary Artery Algorithm Evaluation Framework are provided for comparison with existing techniques. The scores obtained are excellent (97.5% average overlap with ground truth delineated by experts) and demonstrate the high potential of the method in terms of robustness to anomalies and poor image quality.