Brain Tumor CT Image Segmentation Based on SLIC0 Superpixels

被引：0
|
作者：
Wang, Xiaopeng [1 ]
Ma, Peng [1 ]
Zhao, JunJun [1 ]
机构：
[1] Lanzhou Jiaotong Univ, Sch Elect & Informat Engn, Lanzhou 730070, Peoples R China
来源：
2016 9TH INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, BIOMEDICAL ENGINEERING AND INFORMATICS (CISP-BMEI 2016) | 2016年
基金：
中国国家自然科学基金;
关键词：
image segmentation; brain tumor CT images; SLIC0; superpixel; region merging;
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：
The brain tumor CT image segmentation frequently suffers from the fuzzy edges, and manual segmentation mainly relies on doctor's clinical experience. For the purpose to accurately segment brain tumor, a method for brain tumor CT image segmentation based on SLIC0 superpixels is proposed. Firstly, the simple linear iterative clustering version with 0 (SLIC0) is employed to generate superpixels; Secondly, region merging is adopted to merge the similar superpixels according to their gray, and finally segment the brain tumor regions. Experiments show that this method can accurately segment the target tumor, and segmentation accuracy can be adjusted by setting the pixel number of superpixels.
引用
收藏
页码：427 / 431
页数：5
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