Fusion of spatial relationships for guiding recognition, example of brain structure recognition in 3D MRI

被引：26

作者：

Bloch, I

Colliot, O

Camara, O

Géraud, T

机构：

[1] Ecole Natl Super Telecommun Bretagne, Dept TSI, CNRS, UMR 5141,LTCI, F-75013 Paris, France

[2] McGill Univ, McConnell Brain Imaging Ctr, MNI, Montreal, PQ H3A 2B4, Canada

[3] Kings Coll London, London WC2R 2LS, England

[4] EPITA Res & Dev Lab, F-94276 Le Kremlin Bicetre, France

来源：

PATTERN RECOGNITION LETTERS | 2005年 / 26卷 / 04期

关键词：

spatial relationships; fuzzy mathematical morphology; knowledge representation; information fusion; model-based recognition; brain imaging;

D O I：

10.1016/j.patrec.2004.08.009

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Spatial relations play an important role in recognition of structures embedded in a complex environment and for reasoning under imprecision. Several types of relationships can be modeled in a unified way using fuzzy mathematical morphology. Their combination benefits from the powerful framework of fuzzy set theory for fusion tasks and decision making. This paper presents several methods of fusion of information about spatial relationships and illustrates them on the example of model-based recognition of brain structures in 3D magnetic resonance imaging. (C) 2004 Elsevier B.V. All rights reserved.

引用

页码：449 / 457

页数：9

共 24 条

[1]

[Anonymous], FUZZY TECHNIQUES IMA

[2] Inexact graph matching by means of estimation of distribution algorithms [J].