A noisy-smoothing relevance feedback method for content-based medical image retrieval

Huang,Y, Huang,H and Zhang,J 2014, A noisy-smoothing relevance feedback method for content-based medical image retrieval, Multimedia Tools and Applications, vol. 73, no. 3, pp. 1963-1981, doi: 10.1007/s11042-013-1685-4.

Attached Files
Name Description MIMEType Size Downloads

Title A noisy-smoothing relevance feedback method for content-based medical image retrieval
Author(s) Huang,Y
Zhang,JORCID iD for Zhang,J orcid.org/0000-0002-2189-7801
Journal name Multimedia Tools and Applications
Volume number 73
Issue number 3
Start page 1963
End page 1981
Total pages 19
Publisher Springer
Place of publication New York, NY
Publication date 2014-12
ISSN 1380-7501
Keyword(s) CBIR
Fuzzy membership function
Noisy elimination
Relevance feedback
Summary In this paper, we address a new problem of noisy images which present in the procedure of relevance feedback for medical image retrieval. We concentrate on the noisy images, caused by the users mislabeling some irrelevant images as relevant ones, and a noisy-smoothing relevance feedback (NS-RF) method is proposed. In NS-RF, a two-step strategy is proposed to handle the noisy images. In step 1, a noisy elimination algorithm is adopted to identify and eliminate the noisy images. In step 2, to further alleviate the influence of noisy images, a fuzzy membership function is employed to estimate the relevance probabilities of retained relevant images. After noisy handling, the fuzzy support vector machine, which can take into account different relevant images with different relevance probabilities, is adopted to re-rank the images. The experimental results on the IRMA medical image collection demonstrate that the proposed method can deal with the noisy images effectively.
Language eng
DOI 10.1007/s11042-013-1685-4
Field of Research 080504 Ubiquitous Computing
080104 Computer Vision
Socio Economic Objective 890202 Application Tools and System Utilities
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2014, Springer
Persistent URL http://hdl.handle.net/10536/DRO/DU:30071871

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.

Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 0 times in TR Web of Science
Scopus Citation Count Cited 4 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 199 Abstract Views, 2 File Downloads  -  Detailed Statistics
Created: Wed, 22 Apr 2015, 15:24:50 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.