Performance Analysis of Unsupervised Clustering Methods for Brain Tumor Segmentation

被引：0
|
作者：
Jaware, Tushar H. [1 ]
Khanchandani, K. B. [1 ]
机构：
[1] Shri Sant Gajanan Maharaj Coll Engn, Dept E&TC, Shegaon, MS, India
来源：
BRAIN-BROAD RESEARCH IN ARTIFICIAL INTELLIGENCE AND NEUROSCIENCE | 2013年 / 4卷 / 1-4期
关键词：
MRI; clustering; tumor;
D O I：
暂无
中图分类号：
Q189 [神经科学];
学科分类号：
071006 ;
摘要：
Medical image processing is the most challenging and emerging field of neuroscience. The ultimate goal of medical image analysis in brain MRI is to extract important clinical features that would improve methods of diagnosis & treatment of disease. This paper focuses on methods to detect & extract brain tumour from brain MR images. MATLAB is used to design, software tool for locating brain tumor, based on unsupervised clustering methods. K-Means clustering algorithm is implemented & tested on data base of 30 images. Performance evolution of unsupervised clustering methods is presented. Keywords:
引用
收藏
页码：55 / 59
页数：5
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