3D brain tumor segmentation using fuzzy classification and deformable models

被引：0
|
作者：
Khotanlou, H
Atif, J
Colliot, O
Bloch, I
机构：
[1] Ecole Natl Super Telecommun Bretagne, GET, Dept TSI, CNRS,UMR 5142, F-75634 Paris 13, France
[2] McGill Univ, MNI, McConnell Brain Imaging Ctr, Montreal, PQ H3A 2B4, Canada
来源：
FUZZY LOGIC AND APPLICATIONS | 2006年 / 3849卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A new method that automatically detects and segments brain tumors in 3D MR images is presented. An initial detection is performed by a fuzzy possibilistic clustering technique and morphological operations, while a deformable model is used to achieve a precise segmentation. This method has been successfully applied on five 3D images with tumors of different sizes and different locations, showing that the combination of region-based and contour-based methods improves the segmentation of brain tumors.
引用
收藏
页码：312 / 318
页数：7
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