A Modified Genetic Algorithm Based FCM Clustering Algorithm for Magnetic Resonance Image Segmentation

被引：4
作者：
Das, Sunanda [1 ]
De, Sourav [2 ]
机构：
[1] Univ Burdwan, Univ Inst Technol, Dept Comp Sci & Engn, Burdwan 713104, W Bengal, India
[2] Cooch Behar Govt Engn Coll, Dept Comp Sci & Engn, Cooch Behar, W Bengal, India
来源：
PROCEEDINGS OF THE 5TH INTERNATIONAL CONFERENCE ON FRONTIERS IN INTELLIGENT COMPUTING: THEORY AND APPLICATIONS, FICTA 2016, VOL 1 | 2017年 / 515卷
关键词：
Segmentation; Clustering algorithm; Fuzzy C-Means algorithm; Genetic algorithm;
D O I：
10.1007/978-981-10-3153-3_43
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this article, we have devised modified genetic algorithm (MfGA) based fuzzy C-means algorithm, which segment magnetic resonance (MR) images. In FCM, local minimum point can be easily derived for not selecting the centroids correctly. The proposed MfGA improves the population initialization and crossover parts of GA and generate the optimized class levels of the multilevel MR images. After that, the derived optimized class levels are applied as the initial input in FCM. An extensive performance comparison of the proposed method with the conventional FCM on two MR images establishes the superiority of the proposed approach.
引用
收藏
页码：435 / 443
页数：9
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