Brain MRI Segmentation for Tumor Detection using Grammatical Swarm Based Clustering Algorithm

被引：0

作者：

Si, Tapas ^{[1
]}

De, Arunava ^{[2
]}

Bhattacharjee, Anup Kumar ^{[3
]}

机构：

[1] BU Inst Engn, Dept CSE, Bankura, WB, India

[2] Dr BC Roy Engn Coll, Dept IT, Durgapur, W Bengal, India

[3] Natl Inst Technol, Dept ECE, Durgapur, W Bengal, India

来源：

2014 IEEE INTERNATIONAL CONFERENCE ON CIRCUIT, POWER AND COMPUTING TECHNOLOGIES (ICCPCT-2014) | 2014年

关键词：

Magnetic Resonance Image; Brain MRI; Discrete Wavelet Transform; soft thresholding; Grammatical Swarm; Particle Swarm Optimizer; clustering; segmentation; tumor; IMAGE SEGMENTATION;

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

This paper presents segmentation of brain's Magnetic Resonance image for tumor detection using Grammatical Swarm based clustering algorithm. Grammatical Swarm is a variant of Grammatical Evolution which can generate computer programs. First, MR images of brain are de-noised using Discrete Wavelet Transform based soft-thresholding technique. Grammatical Swarm based clustering algorithm is developed to segment the de-noised images to separate the mass lesion or tumor from the non-diseased objects in the image.

引用

页码：1196 / 1201

页数：6

共 25 条

[1] Neural network-based segmentation of magnetic resonance images of the brain [J].