A multi-compartment segmentation framework with homeomorphic level sets

The simultaneous segmentation of multiple objects is an important problem in many imaging and computer vision applications. Various extensions of level set segmentation techniques to multiple objects have been proposed; however, no one method maintains object relationships, preserves topology, is co...

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Veröffentlicht in:2008 IEEE Conference on Computer Vision and Pattern Recognition S. 1 - 6
Hauptverfasser: Xian Fan, Bazin, Pierre-Louis, Prince, Jerry L.
Format: Tagungsbericht Journal Article
Sprache:Englisch
Veröffentlicht: United States IEEE 01.01.2008
Schlagworte:
Anatomy
Application software
Biomedical imaging
Computational complexity
Computer vision
Deformable models
Geometry
Image segmentation
Level set
Topology
ISBN:9781424422425, 1424422426
ISSN:1063-6919, 1063-6919
Online-Zugang:Volltext
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Zusammenfassung:The simultaneous segmentation of multiple objects is an important problem in many imaging and computer vision applications. Various extensions of level set segmentation techniques to multiple objects have been proposed; however, no one method maintains object relationships, preserves topology, is computationally efficient, and provides an object-dependent internal and external force capability. In this paper, a framework for segmenting multiple objects that permits different forces to be applied to different boundaries while maintaining object topology and relationships is presented. Because of this framework, the segmentation of multiple objects each with multiple compartments is supported, and no overlaps or vacuums are generated. The computational complexity of this approach is independent of the number of objects to segment, thereby permitting the simultaneous segmentation of a large number of components. The properties of this approach and comparisons to existing methods are shown using a variety of images, both synthetic and real.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISBN:9781424422425
1424422426
ISSN:1063-6919
1063-6919
DOI:10.1109/CVPR.2008.4587475