A new re-ranking method using enhanced pseudo-relevance feedback for content-based medical image retrieval

Huang, Yonggang, Zhang, Jun, Zhao, Yongwang and Ma, Dianfu 2012, A new re-ranking method using enhanced pseudo-relevance feedback for content-based medical image retrieval, IEICE transactions on information and systems, vol. E95-D, no. 2, pp. 694-698.

Attached Files
Name Description MIMEType Size Downloads

Title A new re-ranking method using enhanced pseudo-relevance feedback for content-based medical image retrieval
Author(s) Huang, Yonggang
Zhang, Jun
Zhao, Yongwang
Ma, Dianfu
Journal name IEICE transactions on information and systems
Volume number E95-D
Issue number 2
Start page 694
End page 698
Total pages 5
Publisher Denshi Jouhou Tsuushin Gakkai
Place of publication Tokyo, Japan
Publication date 2012-02
ISSN 0916-8532
1745-1361
Keyword(s) CBIR
fuzzy SVM ensemble
re-ranking
similarity update
Summary We propose a novel re-ranking method for content-based medical image retrieval based on the idea of pseudo-relevance feedback (PRF). Since the highest ranked images in original retrieval results are not always relevant, a naive PRF based re-ranking approach is not capable of producing a satisfactory result. We employ a two-step approach to address this issue. In step 1, a Pearson's correlation coefficient based similarity update method is used to re-rank the high ranked images. In step 2, after estimating a relevance probability for each of the highest ranked images, a fuzzy SVM ensemble based approach is adopted to re-rank the images. The experiments demonstrate that the proposed method outperforms two other re-ranking methods.
Language eng
Field of Research 089999 Information and Computing Sciences not elsewhere classified
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2012, The Institute of Electronics, Information and Communication Engineers
Persistent URL http://hdl.handle.net/10536/DRO/DU:30047014

Document type: Journal Article
Collection: School of Information Technology
Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Versions
Version Filter Type
Access Statistics: 52 Abstract Views, 7 File Downloads  -  Detailed Statistics
Created: Mon, 13 Aug 2012, 13:00:23 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.