NDLI: Content Based Image Retrieval for MR Image Studies of Brain Tumors

Content Provider	IEEE Xplore Digital Library
Author	Dube, S. El-Saden, S. Cloughesy, T.F. Sinha, U.
Copyright Year	2006
Description	Author affiliation: Med. Imaging Informatics Group, California Univ., Los Angeles, CA (Dube, S.; El-Saden, S.)
Abstract	This work proposes a methodology for content-based image retrieval of glioblastoma multiforme (GBM) and non-GBM tumors. Regions containing GBM lesions from 40 patients and non-GBM lesions from 20 patients were manually segmented from MR imaging studies (T1 post-contrast and T2 weighted channels) to form the training set. In addition to the two acquired channels, a composite image was formed by an image fusion method. Data reduction techniques, principal component analysis (PCA) and linear discriminant analysis (LDA), were applied on the training sets (T1 post, T2, composite, and multi-channel combining the PCA features from T1 post and T2). The retrieval accuracy was evaluated using a 'leave-one-out' strategy with query images belonging to 'normal', 'GBM' and 'non-GBM' classes. Several combinations of the similarity metric and classifier were used: Euclidean similarity measures with k-means classifier for the PCA and LDA features and support vector machine (SVM) nonlinear classifier (radial basis function kernel) with the PCA derived features. The SVM classifier served as a comparison of nonlinear techniques vs. linear ones. Multi-channel PCA was 100% accurate in classifying a query image as either 'normal' or 'abnormal'. The highest accuracy in classification of tumor grade (GBM or other Grade 3) was 77% and was achieved by SVM coupled with the PCA features. The proposed algorithm intent is to be integrated into an automated decision support system for MR brain tumor studies
Sponsorship	IEEE EMB
Starting Page	3337
Ending Page	3340
File Size	254561
Page Count	4
File Format	PDF
ISBN	1424400325
ISSN	1557170X
DOI	10.1109/IEMBS.2006.260262
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-08-30
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image retrieval Content based retrieval Neoplasms Principal component analysis Support vector machines Support vector machine classification Linear discriminant analysis Lesions Image segmentation Image fusion
Content Type	Text
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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