Topologically controlled segmentation of 3D magnetic resonance images of the head by using morphological operators

被引：37

作者：

Dokládal, P

Bloch, I

Couprie, M

Ruijters, D

Urtasun, R

Garnero, L

机构：

[1] Ecole Natl Super Telecommun Bretagne, Dept TSI, CNRS, URA 820, F-75013 Paris, France

[2] Ecole Natl Super Telecommun Bretagne, IFR 49, F-75013 Paris, France

[3] Ecole Super Ingn Elect & Electrotech, Lab Algorithm & Architecture Syst Informat, F-93162 Noisy Le Grand, France

[4] Hop La Pitie Salpetriere, CNRS, LENA, UPR 640, F-75651 Paris 13, France

[5] Hop La Pitie Salpetriere, IFR 49, F-75651 Paris 13, France

来源：

PATTERN RECOGNITION | 2003年 / 36卷 / 10期

关键词：

brain imaging; 3D segmentation; mathematical morphology; topological constraints;

D O I：

10.1016/S0031-3203(03)00118-3

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 proposes a new data-driven segmentation technique of 3D T1-weighted magnetic resonance scans of human head. This technique serves to the construction of individual head models. Several structures of the head are extracted. The morphology-oriented approach combined with an extensive use of topological constraints provides a robust and automatic method requiring minimum user intervention. This new approach is suitable to applications where the topology is one of the main constraints. The originality of the approach lies in the satisfaction of such constraints and in an effort towards robustness. (C) 2003 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.

引用

页码：2463 / 2478

页数：16

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