Authors:
R. Varaprasada Rao,JayachandraPrasad Talari,DOI NO:
https://doi.org/10.26782/jmcms.2020.08.00062Keywords:
Medical Image Retrieval,Non Sub-sampled Shearlet Transform,Local Multiscale and Directional Frequency Encoded Binary Pattern,Local Wavelet Pattern,Euclidean distance,Abstract
In this work, a new feature descriptor has been proposed for efficient CT Medical Image Retrieval (MIR). Non Subsampled Pyramid (NSP) of Non Sub-sampled Shearlet Transform (NSST) has been carried out for multiscale and multidirectional image decomposition into low and high frequency sub bands.A newfeature descriptor “Local Multiscale and Multidirectional Frequency Encoded Binary Pattern (LMSMDFEBP)” has been proposed to obtain the local directional information in each sub-bands of images.Feature vectors of database and query images have been obtained from the histogram of LMSMDFEBP. The Euclidean distance has been evaluated to analyse the similarity between query and database feature vectors. Two tests have been carried out on publicly available EXACT-09 and TCIA CT databases to assess the performance of proposed method. The proposed approach shows an improvement of ARP values 3.36% and 8.98% for the EXACT-09 and TCIA-CT respectively, compared with the existing Local Wavelet Pattern (LWP).Refference:
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