A new content-based medical image retrieval system based on wavelet transform and multidimensional wald-wolfowitz runs test

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dc.contributor.authorNakaram, Phatsarun
dc.contributor.authorLeauhatong, Thurdsak
dc.date.accessioned2026-08-06T10:05:18Z
dc.date.available2026-08-06T10:05:18Z
dc.date.issued2012-12-01
dc.description.abstractRecently, one of the authors proposed a new similarity measure, called weighted multidimensional Wald and Wolfowitz (MWW) runs test, for the content-based color image retrieval system. The algorithm outperforms conventional similarity measures for comparing two color images. In this paper, we propose a new content-based medical image retrieval system based on discrete wavelet transform (DWT) symlet and the weighted MWW runs test. The DWT is used to extracted texture features of the medical images. The weighted MWW runs test is used to compare distributions of texture features of two medical images. Our experiments were performed on 1,000 medical images from image retrieval in medical applications (IRMA). The experimental results show promisingly efficient to retrieve the medical images. ©2012 IEEE.
dc.identifier.citation5th 2012 Biomedical Engineering International Conference Bmeicon 2012, 2012
dc.identifier.doi10.1109/BMEiCon.2012.6465501
dc.identifier.other2-s2.0-84875103327
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/4502
dc.source5th 2012 Biomedical Engineering International Conference Bmeicon 2012
dc.subjectK-mean clustering algorithm
dc.subjectWald and wolfowitz runs test
dc.subjectWavelet transform
dc.titleA new content-based medical image retrieval system based on wavelet transform and multidimensional wald-wolfowitz runs test
dc.typeConference Paper

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