A Relevance Feedback Method in Medical Image Retrieval Based on Bayesian Theory

Author

Zhang, Quan ; Tai, Xiao-ying

Author_Institution

Dept. of Comput. Sci., Ningbo Univ., Ningbo

Volume

1

fYear

2008

fDate

27-30 May 2008

Firstpage

840

Lastpage

844

Abstract

Earlier researches have proved that the gray co-occurrence matrix representing the texture feature is more effective than many other features in the sternum image retrieval and the relevance feedback technology implementing man-machine interactive retrieval enhance retrieval efficiency. Based on these conclusions, in this paper, a new relevance feedback method based on minimal Bayesian error rate in sternum image retrieval is proposed. The comparison of feedback retrieval result shows the approach is effective.

Keywords

Bayes methods; medical information systems; relevance feedback; Bayesian theory; Rocchio relevance feedback technology; medical image retrieval; minimal Bayesian error rate; moving query feedback method; partition texture retrieval; relevance feedback method; sternum image retrieval; Bayesian methods; Biomedical engineering; Biomedical imaging; Euclidean distance; Feedback; Image retrieval; Pixel; Spatial resolution; Sternum; Symmetric matrices; Bayesian; gray co-occurrence matrix; sternum image;

fLanguage

English

Publisher

ieee

Conference_Titel

BioMedical Engineering and Informatics, 2008. BMEI 2008. International Conference on

Conference_Location

Sanya

Print_ISBN

978-0-7695-3118-2

Type

conf

DOI

10.1109/BMEI.2008.69

Filename

4548789