Content based medical image retrieval using dictionary learning

Mettu, Srinivas and R, Ramu Naidu and Challa, Subrahmanya Sastry and C, Krishna Mohan (2015) Content based medical image retrieval using dictionary learning. Neurocomputing, 168. pp. 880-895. ISSN 0925-2312

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n this paper, a clustering method using dictionary learning is proposed to group large medical databases. An approach grouping similar images into clusters that are sparsely represented by the dictionaries and learning dictionaries simultaneously via K-SVD is proposed. A query image is matched with the existing dictionaries to identify the dictionary with the sparsest representation using an Orthogonal Matching Pursuit (OMP) algorithm. Then images in the cluster associated with this dictionary are compared using a similarity measure to retrieve images similar to the query image. The main features of the method are that it requires no training data and works well on the medical databases which are not restricted to specific context. The performance of the proposed method is examined on IRMA test image database. The experimental results demonstrate the efficacy of the proposed method in the retrieval of medical images.

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IITH Creators:
IITH CreatorsORCiD
Challa, Subrahmanya SastryUNSPECIFIED
Item Type: Article
Additional Information: Authors would like to thank Dr. T.M. Deserno, Department of Medical Informatics, RWTH Aachen, Germany for making the original IRMA Database available for research purposes. One of the authors (CSS) is thankful to the CSIR for its support (25(0219)/13/EMR-II). Authors are grateful to the anonymous reviewers for their thorough review and constructive comments, which improved the manuscript substantially. Finally, authors thank Prof. Andrea Vedaldi for making the software of Vlad and Fisher vectors available.
Uncontrolled Keywords: Clustering; Content based image retrieval; Dictionary learning; Rotation invariance; Sparse representation; K-SVD; OMP
Subjects: Computer science > Special computer methods
Divisions: Department of Computer Science & Engineering
Department of Mathematics
Depositing User: Team Library
Date Deposited: 07 Jul 2015 06:48
Last Modified: 01 Sep 2017 09:09
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