Segmentation and Classification Techniques of Medical Images using Innovated Hybridized Techniques - A Study

被引:0
作者
Sharma, Rajesh R. [1 ]
Sungheetha, Akey [2 ]
机构
[1] Hindusthan Coll Engg & Tech, Dept Informat Technol, Coimbatore, Tamil Nadu, India
[2] Karpagam Coll Engn, Dept Informat Technol, Coimbatore, Tamil Nadu, India
来源
PROCEEDINGS OF 2017 11TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS AND CONTROL (ISCO 2017) | 2017年
关键词
Classification; Segmentation; Feature Extraction; SVM; RGSA; GWO; LIVER SEGMENTATION; SELECTION;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Over the years, the growth in medical image processing is increasing in a tremendous manner. The rate of increasing diseases with respect to various types of cancer and other related human problems paves the way for the development in biomedical research. Thus processing and analyzing these medical images is of high importance for clinical diagnosis. This work focuses on performing effective classification of brain tumor images and segmentation of live disease images employing the proposed hybrid intelligent techniques. The challenges and objectives on design of feature extraction, image classification and segmentation for medical images are discussed.
引用
收藏
页码:192 / 196
页数:5
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