Gooßen, AndréAndréGooßenPralow, ThomasThomasPralowGrigat, Rolf-RainerRolf-RainerGrigat2021-08-032021-08-032010-10-25Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 6357 LNCS: 132-139 (2010-10-25)http://hdl.handle.net/11420/10032Orthopaedic examinations are a major reason for radiographic image acquisition. For many diagnostic problems measurements have to be computed from the recorded radiographs. As this task is time-consuming and lacks objectivity, it is desirable to perform these measurements automatically via so-called computational imaging. This requires robust and accurate methods trained and proven on clinical data. We propose a fully automatic technique and present the three complementing stages of our segmentation algorithm. We evaluated the proposed method on more than 200 clinical images and achieve robust and precise delineations, well-suited for automated computation of orthopaedic measurements. © 2010 Springer-Verlag Berlin Heidelberg.enComputational ImagingCost Path OptimizationDeformable ModelsDigital X-RayGeneralized Hough TransformRadiographyTechnikMedizinConference Paper10.1007/978-3-642-15948-0_17Other