DocumentCode :
2362751
Title :
A variational framework for joint segmentation and registration
Author :
Yezzi, Anthony ; Zöllei, Lilla ; Kapur, Tizna
Author_Institution :
Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
fYear :
2001
fDate :
2001
Firstpage :
44
Lastpage :
51
Abstract :
Traditionally, segmentation and registration have been solved as two independent problems, even though it is often the case that the solution to one impacts the solution to the other. In this paper, we introduce a geometric, variational framework that uses active contours to simultaneously segment and register features from multiple images. The key observation is that multiple images may be segmented by evolving a single contour as well as the mappings of that contour into each image. To the best of our knowledge, this is the first attempt at interleaving segmentation and registration in such a framework
Keywords :
Jacobian matrices; curve fitting; gradient methods; image registration; image segmentation; medical image processing; variational techniques; 2D case; 3D case; Jacobian matrix; active contours; anatomical constraints; contour mappings; energy functions; geometric variational framework; gradient flows; image registration; image segmentation; interleaving segmentation and registration; level set methodology; low-level segmentation methods; medical image analysis; multiple images; objective functions; parametric representations; region based models; single contour evolution; Active contours; Anatomical structure; Anatomy; Biomedical imaging; Image edge detection; Image segmentation; Interleaved codes; Laboratories; Shape; Visualization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mathematical Methods in Biomedical Image Analysis, 2001. MMBIA 2001. IEEE Workshop on
Conference_Location :
Kauai, HI
Print_ISBN :
0-7695-1336-0
Type :
conf
DOI :
10.1109/MMBIA.2001.991698
Filename :
991698
Link To Document :
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