Brain MR Image Segmentation Based on Gaussian Filtering and Improved FCM Clustering Algorithm

被引：0

作者：

Wan, Chunyuan ^{[1
]}

Ye, Mingquan ^{[1
]}

Yao, Chuanwen ^{[1
]}

Wu, Changrong ^{[2
]}

机构：

[1] Wannan Med Coll, Sch Med Informat, Wuhu, Peoples R China

[2] Anhui Normal Univ, Sch Math & Comp Sci, Wuhu, Peoples R China

来源：

2017 10TH INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, BIOMEDICAL ENGINEERING AND INFORMATICS (CISP-BMEI) | 2017年

基金：

中国国家自然科学基金;

关键词：

brain MR image; image segmentation; Gaussian filtering; fuzzy C-means clustering; gray histogram; C-MEANS ALGORITHM; AUTOMATIC SEGMENTATION; SPATIAL INFORMATION; LOCAL INFORMATION; FUZZY; INITIALIZATION; OPTIMIZATION;

D O I：

暂无

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

Traditional fuzzy C-means (FCM) clustering method is not able to get the desired results of brain segmentation in the brain magnetic resonance (MR) image. In this paper, a new method of brain image segmentation based on Gaussian filtering and FCM clustering algorithm is proposed. The method adopted Gaussian filtering to remove noise and the initial cluster center was determined by the gray histograms to obtain. Using this method, 20 samples of brain MR images with 9% and 5% noise interference provided by Brain Web were segmented. The experimental results showed the proposed method was accuracy and efficiency.

引用

页数：5

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