DocumentCode
1814972
Title
TOADS: topology-preserving, anatomy-driven segmentation
Author
Bazin, Pierre-Louis ; Pham, Dzung L.
Author_Institution
Dept. of Radiol. & Radiol. Sci., Johns Hopkins Univ., Baltimore, MD
fYear
2006
fDate
6-9 April 2006
Firstpage
327
Lastpage
330
Abstract
This paper presents a new algorithm for object segmentation in medical images that respects the topological properties and anatomical relationships of structures as given by a template. The technique combines advantages of tissue classification, digital topology, and image registration to handle any given topology and enforces object-level relationships with little constraint over the geometry. It is applied to cortical segmentation and validated on simulated and real images
Keywords
biological tissues; brain; image classification; image registration; image segmentation; medical image processing; TOADS; cortical segmentation; digital topology; image registration; medical images; object segmentation; tissue classification; topology-preserving anatomy-driven segmentation; Anatomy; Biomedical imaging; Geometry; Image registration; Image segmentation; Object segmentation; Radiology; Skeleton; Surface morphology; Topology;
fLanguage
English
Publisher
ieee
Conference_Titel
Biomedical Imaging: Nano to Macro, 2006. 3rd IEEE International Symposium on
Conference_Location
Arlington, VA
Print_ISBN
0-7803-9576-X
Type
conf
DOI
10.1109/ISBI.2006.1624919
Filename
1624919
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