A new content-based medical image retrieval system based on wavelet transform and multidimensional wald-wolfowitz runs test - Nakaram, Phatsarun; Leauhatong, Thurdsak (My University, 2012)
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. ©2012 IEEE.
Keywords: K-mean clustering algorithm; Wald and wolfowitz runs test; Wavelet transform