Mutual Information Based Feature Selection for Medical Image Retrieval

被引:0
作者
Zhi, Lijia [1 ]
Zhang, Shaomin [1 ]
Li, Yan [1 ]
机构
[1] North Minzu Univ, Sch Comp Sci & Engn, Yinchuan 750021, Peoples R China
来源
NINTH INTERNATIONAL CONFERENCE ON GRAPHIC AND IMAGE PROCESSING (ICGIP 2017) | 2018年 / 10615卷
基金
中国国家自然科学基金;
关键词
Medical image retrieval; local and global features; mutual information; maximal dependency; feature selection; RECOGNITION;
D O I
10.1117/12.2302663
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
In this paper, authors propose a mutual information based method for lung CT image retrieval. This method is designed to adapt to different datasets and different retrieval task. For practical applying consideration, this method avoids using a large amount of training data. Instead, with a well-designed training process and robust fundamental features and measurements, the method in this paper can get promising performance and maintain economic training computation. Experimental results show that the method has potential practical values for clinical routine application.
引用
收藏
页数:7
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