3D brain tumor segmentation in MRI using fuzzy classification, symmetry analysis and spatially constrained deformable models

被引：164

作者：

Khotanlou, Hassan ^{[1
]}

Colliot, Olivier ^{[2
]}

Atif, Jamal ^{[3
]}

Bloch, Isabelle ^{[1
]}

机构：

[1] TELECOM ParisTech ENST, CNRS, UMR 5141, LTCI,IFR 49, Paris, France

[2] Univ Paris 06, CNRS, Hop Pitie Salpetriere,UPR 640, Cognit Neurosci & Brain Imaging Lab,IFR 49, Paris, France

[3] Univ Antilles Guyane, GRER, F-97300 Cayenne, France

来源：

FUZZY SETS AND SYSTEMS | 2009年 / 160卷 / 10期

关键词：

Brain tumor; Segmentation; Deformable model; Spatial relations; Symmetry plane;

D O I：

10.1016/j.fss.2008.11.016

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

We propose a new general method for segmenting brain tumors in 3D magnetic resonance images. Our method is applicable to different types of tumors. First, the brain is segmented using a new approach, robust to the presence of tumors. Then a first tumor detection is performed, based on selecting asymmetric areas with respect to the approximate brain symmetry plane and fuzzy classification. Its result constitutes the initialization of a segmentation method based on a combination of a deformable model and spatial relations, leading to a precise segmentation of the tumors. Imprecision and variability are taken into account at all levels, using appropriate fuzzy models. The results obtained on different types of tumors have been evaluated by comparison with manual segmentations. (C) 2008 Elsevier B.V. All rights reserved.

引用

页码：1457 / 1473

页数：17

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