DocumentCode
1964408
Title
Using deformable models to segment complex structures under geometric constraints
Author
Gout, Christian ; Vieira-Teste, Sylvie
Author_Institution
Dept. de Math. Appl., Pau Univ., France
fYear
2000
fDate
2000
Firstpage
101
Lastpage
105
Abstract
In many problems of medical or geophysical interest, when trying to segment an image, one has to deal with data that exhibit very complex structures. This problem occurs when images have discontinuities: in medical imaging (fractures radiography), in geophysics (segmentation of a set of layers and faults) etc. To solve this problem, we present a segmentation method which uses deformable models. The originality of the method is that we have interpolation data and triple points that involves making some geometric constraints on the model. We also propose a method for noise removal because it is well known that most of these images are noisy, that could hinder the segmentation. Numerical results on geophysical images are given
Keywords
computational geometry; data structures; geophysical signal processing; image segmentation; interpolation; medical image processing; complex data structures; deformable models; geometric constraints; geophysical image; image discontinuities; image segmentation; interpolation data; medical image; noisy images; triple points; Active contours; Arthritis; Deformable models; Image segmentation; Independent component analysis; Integrated circuit noise; Level set; Minimization methods; Shape; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Analysis and Interpretation, 2000. Proceedings. 4th IEEE Southwest Symposium
Conference_Location
Austin, TX
Print_ISBN
0-7695-0595-3
Type
conf
DOI
10.1109/IAI.2000.839580
Filename
839580
Link To Document