Integration of fuzzy spatial relations in deformable models - Application to brain MRI segmentation

被引:97
作者
Colliot, Olivier [1 ]
Camara, Oscar [1 ]
Bloch, Isabelle [1 ]
机构
[1] CNRS, Ecole Natl Super Telecommun, Dept TSI, UMR 5141,LTCI, F-75634 Paris 13, France
关键词
spatial relations; deformable models; fuzzy sets; MRI; subcortical structures;
D O I
10.1016/j.patcog.2006.02.022
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents a general framework to integrate a new type of constraints, based on spatial relations, in deformable models. In the proposed approach, spatial relations are represented as fuzzy subsets of the image space and incorporated in the deformable model as a new external force. Three methods to construct an external force from a fuzzy set representing a spatial relation are introduced and discussed. This framework is then used to segment brain subcortical structures in magnetic resonance images (MRI). A training step is proposed to estimate the main parameters defining the relations. The results demonstrate that the introduction of spatial relations in a deformable model can substantially improve the segmentation of structures with low contrast and ill-defined boundaries. (c) 2006 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:1401 / 1414
页数:14
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