DocumentCode :
1566495
Title :
A Hierarchical Topological Knowledge Based Image Segmentation Approach Optimizing the use of Contextual Regions of Interest : Illustration for Medical Image Analysis
Author :
Fasquel, J. -B. ; Agnus, V. ; Soler, Luciana ; Marescaux, J.
Author_Institution :
IRCAD, Strasbourg, France
fYear :
2006
Firstpage :
777
Lastpage :
780
Abstract :
This paper concerns image segmentation and presents a method to automically determine optimal regions of interest (ROI) according to topological information. The use of ROI avoids the processing of irrelevant image points, therefore improving and accelerating segmentations. ROI determination is based on the optimal use of both the a priori knowledge about topological structure of an image and the contextual information. Contextual information concerns the nature of already segmented regions in the case of the hierarchical segmentation approach we consider. We describe this general purpose method and propose a formulation for the optimal determination of ROIs according to both informations. Then, we illustrate the use and the implementation of such a method in the particular case of medical image segmentation.
Keywords :
image segmentation; medical image processing; ROI; contextual information; image segmentation; medical image analysis; regions of interest; topological information; topological knowledge; Acceleration; Biomedical image processing; Biomedical imaging; Data mining; Histograms; Image analysis; Image segmentation; Interactive systems; Photometry; Topology; Biomedical image processing; Image segmentation; Interactive systems; Knowledge based systems; Topology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing, 2006 IEEE International Conference on
Conference_Location :
Atlanta, GA
ISSN :
1522-4880
Print_ISBN :
1-4244-0480-0
Type :
conf
DOI :
10.1109/ICIP.2006.312517
Filename :
4106645
Link To Document :
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