Topology preserving tissue classification with fast marching and topology templates

Authors:
Pierre-Louis Bazin;Dzung L. Pham
Affiliations:
Laboratory of Medical Image Computing, Neuroradiology Division, Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD;Laboratory of Medical Image Computing, Neuroradiology Division, Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD
Venue:
IPMI'05 Proceedings of the 19th international conference on Information Processing in Medical Imaging
Year:
2005

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Abstract

This paper presents a novel approach for object segmentation in medical images that respects the topological relationships of multiple structures as given by a template. The algorithm combines advantages of tissue classification, digital topology, and level-set evolution into a topology-invariant multiple-object fast marching method. The technique can handle any given topology and enforces object-level relationships with little constraint over the geometry. Applied to brain segmentation, it sucessfully extracts gray matter and white matter structures with the correct spherical topology without topology correction or editing of the sub-cortical structures.