Title :
A new content-based medical image retrieval system based on wavelet transform and multidimensional Wald-Wolfowitz runs test
Author :
Nakaram, P. ; Leauhatong, Thurdsak
Author_Institution :
Sch. of Electron. Eng., King Mongkut´´s Inst. of Technol. Ladkrabang, Bangkok, Thailand
Abstract :
Recently, 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.
Keywords :
discrete wavelet transforms; image colour analysis; image retrieval; image texture; medical computing; DWT; IRMA; Image Retrieval in Medical Applications; color image comparison; content based color image retrieval system; content based medical image retrieval system; discrete wavelet transform; multidimensional Wald-Wolfowitz runs test; similarity measure; symlet; texture feature distributions; weighted MWW runs test; Biomedical imaging; Databases; Diseases; Manganese; Wald and Wolfowitz runs test; k-mean clustering algorithm; wavelet transform;
Conference_Titel :
Biomedical Engineering International Conference (BMEiCON), 2012
Conference_Location :
Ubon Ratchathani
Print_ISBN :
978-1-4673-4890-4
DOI :
10.1109/BMEiCon.2012.6465501