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3D local circular difference patterns for biomedical image retrieval

3D local circular difference patterns for biomedical image retrieval In this paper, three-dimensional local circular difference patterns (3D LCDP) and three-dimensional local circular difference wavelet patterns (3D LCDWP) are proposed for retrieval of biomedical images. The standard patterns are used to correlate gray value of center pixel with neighboring pixels. In the proposed approach, 3D volume is generated for calculating local circular difference patterns with the help of three planes obtained from original image. In case of color image, RGB channels are used as three planes and Gaussian filter banks of different resolution for gray level image. From this 3D volume, LCDP values are obtained by calculating relationship between center pixel and neighboring pixels in five different directions. Finally, feature vector is generated using histogram. The performance is evaluated using different medical databases: (i) open access series of imaging studies MRI database, (ii) International early lung cancer action program and vision and image analysis research groups CT scans, (iii) MESSIDOR-Retinal image database. The results are compared with existing biomedical image retrieval techniques by considering average retrieval precision and average retrieval rate as evaluation parameters. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Multimedia Information Retrieval Springer Journals

3D local circular difference patterns for biomedical image retrieval

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Publisher
Springer Journals
Copyright
Copyright © 2019 by Springer-Verlag London Ltd., part of Springer Nature
Subject
Computer Science; Multimedia Information Systems; Information Storage and Retrieval; Information Systems Applications (incl.Internet); Data Mining and Knowledge Discovery; Image Processing and Computer Vision; Database Management
ISSN
2192-6611
eISSN
2192-662X
DOI
10.1007/s13735-019-00170-1
Publisher site
See Article on Publisher Site

Abstract

In this paper, three-dimensional local circular difference patterns (3D LCDP) and three-dimensional local circular difference wavelet patterns (3D LCDWP) are proposed for retrieval of biomedical images. The standard patterns are used to correlate gray value of center pixel with neighboring pixels. In the proposed approach, 3D volume is generated for calculating local circular difference patterns with the help of three planes obtained from original image. In case of color image, RGB channels are used as three planes and Gaussian filter banks of different resolution for gray level image. From this 3D volume, LCDP values are obtained by calculating relationship between center pixel and neighboring pixels in five different directions. Finally, feature vector is generated using histogram. The performance is evaluated using different medical databases: (i) open access series of imaging studies MRI database, (ii) International early lung cancer action program and vision and image analysis research groups CT scans, (iii) MESSIDOR-Retinal image database. The results are compared with existing biomedical image retrieval techniques by considering average retrieval precision and average retrieval rate as evaluation parameters.

Journal

International Journal of Multimedia Information Retrieval – Springer Journals

Published: Apr 3, 2019

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