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Erschienen in:
2011 | OriginalPaper | Buchkapitel
Conditional Point Distribution Models
verfasst von : Kersten Petersen, Mads Nielsen, Sami S. Brandt
Erschienen in: Medical Computer Vision. Recognition Techniques and Applications in Medical Imaging
Verlag: Springer Berlin Heidelberg
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In this paper, we propose an efficient method for drawing shape samples using a point distribution model (PDM) that is conditioned on given points. This technique is suited for sample-based segmentation methods that rely on a PDM,
e.g.
[6], [2] and [3]. It enables these algorithms to effectively constrain the solution space by considering a small number of user inputs – often one or two landmarks are sufficient. The algorithm is easy to implement, highly efficient and usually converges in less than 10 iterations. We demonstrate how conditional PDMs based on a single user-specified vertebra landmark significantly improve the aorta and vertebrae segmentation on standard lateral radiographs. This is an important step towards a fast and cheap quantification of calcifications on X-ray radiographs for the prognosis and diagnosis of cardiovascular disease (CVD) and mortality.