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IPMI
2007
Springer

Spine Detection and Labeling Using a Parts-Based Graphical Model

9 years 11 months ago
Spine Detection and Labeling Using a Parts-Based Graphical Model
Abstract. The detection and extraction of complex anatomical structures usually involves a trade-off between the complexity of local feature extraction and classification, and the complexity and performance of the subsequent structural inference from the viewpoint of combinatorial optimization. Concerning the latter, computationally efficient methods are of particular interest that return the globally-optimal structure. We present an efficient method for part-based localization of anatomical structures which embeds contextual shape knowledge in a probabilistic graphical model. It allows for robust detection even when some of the part detections are missing. The application scenario for our statistical evaluation is spine detection and labeling in magnetic resonance images.
Stefan Schmidt, Jörg H. Kappes, Martin Bergth
Added 08 Jun 2010
Updated 08 Jun 2010
Type Conference
Year 2007
Where IPMI
Authors Stefan Schmidt, Jörg H. Kappes, Martin Bergtholdt, Vladimir Pekar, Sebastian P. M. Dries, Daniel Bystrov, Christoph Schnörr
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