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Proceedings Paper

Robust algorithms for anatomic plane primitive detection in MR
Author(s): Maneesh Dewan; Yiqiang Zhan; Zhigang Peng; Xiang Sean Zhou
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Paper Abstract

One of primary challenges in the medical image data analysis is the ability to handle abnormal, irregular and/or partial cases. In this paper, we present two different robust algorithms towards the goal of automatic planar primitive detection in 3D volumes. The overall algorithm is a bottoms-up approach starting with the anatomic point primitives (or landmarks) detection. The robustness in computing the planar primitives is built in through both a novel consensus-based voting approach, and a random sampling-based weighted least squares regression method. Both these approaches remove inconsistent landmarks and outliers detected in the landmark detection step. Unlike earlier approaches focused towards a particular plane, the presented approach is generic and can be easily adapted to computing more complex primitives such as ROIs or surfaces. To demonstrate the robustness and accuracy of our approach, we present extensive results for automatic plane detection (Mig-Sagittal and Optical Triangle planes) in brain MR-images. In comparison to ground truth, our approach has marginal errors on about 90 patients. The algorithm also works really well under adverse conditions of arbitrary rotation and cropping of the 3D volume. In order to exhibit generalization of the approach, we also present preliminary results on intervertebrae-plane detection for 3D spine MR application.

Paper Details

Date Published: 27 February 2009
PDF: 5 pages
Proc. SPIE 7260, Medical Imaging 2009: Computer-Aided Diagnosis, 72601C (27 February 2009); doi: 10.1117/12.813735
Show Author Affiliations
Maneesh Dewan, Siemens Medical Solutions USA, Inc. (United States)
Yiqiang Zhan, Siemens Medical Solutions USA, Inc. (United States)
Zhigang Peng, Siemens Medical Solutions USA, Inc. (United States)
Xiang Sean Zhou, Siemens Medical Solutions USA, Inc. (United States)

Published in SPIE Proceedings Vol. 7260:
Medical Imaging 2009: Computer-Aided Diagnosis
Nico Karssemeijer; Maryellen L. Giger, Editor(s)

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