12 May 2004 A 3D statistical shape model of the pelvic bone for segmentation
Author Affiliations +
Proceedings Volume 5370, Medical Imaging 2004: Image Processing; (2004); doi: 10.1117/12.534145
Event: Medical Imaging 2004, 2004, San Diego, California, United States
Statistical models of shape are a promising approach for robust and automatic segmentation of medical image data. This work describes the construction of a statistical shape model of the pelvic bone. An interactive approach is proposed for solving the correspondence problem which is able to handle shapes of arbitrary topology, suitable for the genus 3 surface of the pelvic bone. Moreover it allows to specify corresponding anatomical features as boundary constraints to the matching process. The model's capability for segmentation was tested on a set of 23 CT data sets. Quantitative results will be presented, showing that the model is well suited for segmentation purposes.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hans Lamecker, Martin Seebass, Hans-Christian Hege, Peter Deuflhard, "A 3D statistical shape model of the pelvic bone for segmentation", Proc. SPIE 5370, Medical Imaging 2004: Image Processing, (12 May 2004); doi: 10.1117/12.534145; https://doi.org/10.1117/12.534145

Data modeling


Image segmentation

Statistical modeling

3D modeling

Statistical analysis

Image processing

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