Document Detail


An implementation of a CBIR system based on SVM learning scheme.
MedLine Citation:
PMID:  23276155     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Content-based image retrieval (CBIR) has been one of the most active areas of research. The retrieval principle of CBIR systems is based on visual features such as colour, texture and shape or the semantic meaning of the images. A CBIR system can be used to locate medical images in large databases. This paper presents a CBIR system for retrieving digital human brain magnetic resonance images (MRI) based on textural features and the support vector machine (SVM) learning method. This system can retrieve similar images from the database in two groups: normal and tumoural. This research uses the knowledge of the CBIR approach to the application of medical decision support and discrimination between the normal and abnormal medical images based on features. This study presents and compares the results of the proposed method with the CBIR systems used in recent works. The experimental results indicate that the proposed method is reliable and has high image retrieval efficiency compared with the previous works.
Authors:
Mana Tarjoman; Emad Fatemizadeh; Kambiz Badie
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Journal of medical engineering & technology     Volume:  37     ISSN:  1464-522X     ISO Abbreviation:  J Med Eng Technol     Publication Date:  2013 Jan 
Date Detail:
Created Date:  2013-01-01     Completed Date:  2013-06-10     Revised Date:  2013-06-14    
Medline Journal Info:
Nlm Unique ID:  7702125     Medline TA:  J Med Eng Technol     Country:  England    
Other Details:
Languages:  eng     Pagination:  43-7     Citation Subset:  IM    
Affiliation:
Department of Engineering, Abhar Branch, Islamic Azad University, Abhar, Iran. manatarjoman@gmail.com
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MeSH Terms
Descriptor/Qualifier:
Brain / anatomy & histology
Brain Neoplasms / pathology
Databases, Factual
Humans
Image Processing, Computer-Assisted / methods*
Magnetic Resonance Imaging / methods*
Support Vector Machines*
Comments/Corrections
Erratum In:
J Med Eng Technol. 2013 Apr;37(3):235

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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