Analysis of Multimodality Brain Images using Machine Learning Techniques

被引:0
作者
Kavitha, S. [1 ]
Thyagharajan, K. K. [2 ]
机构
[1] SSN Coll Engn, Dept CSE, Chennai 603110, Tamil Nadu, India
[2] RMD Engn Coll, Dept ECE, Chennai 601206, Tamil Nadu, India
来源
2015 INTERNATIONAL CONFERENCE ON COMMUNICATIONS AND SIGNAL PROCESSING (ICCSP) | 2015年
关键词
Classification; Fusion; Pulse Coupled Neural Network; Support Vector Machine;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In the recent era, due to the technological growth and requirement, various modern medical imaging equipments are developed with different imaging principles. Analyzing these images manually in different dimensions has been proven critical for physicians, biologists and radiologists to seek answers for diagnosis problems. Presently problems exists at each level of imaging across different imaging modalities/scales, registration, fusion, image analysis, pattern recognition, image mining, visualization, reconstruction and informatics methods. This paper is focused on multimodality brain images and its analysis at different stages of process such as fusion, classification and understanding using machine learning techniques. The importance of fusion is illustrated using the result of classification and the need of understanding technique is introduced for further research.
引用
收藏
页码:1482 / 1486
页数:5
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