A Content Based Approach to Medical X-Ray Image Retrieval using Texture Features

INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY

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Field Value
 
Title A Content Based Approach to Medical X-Ray Image Retrieval using Texture Features
 
Creator Ganesan, Sumathi
Subashini, T.S.
 
Subject Content based image retrieval; back propagation neural network; support vector machine; gray level co-occurrence matrix and city block distance method
 
Description Of late, the amount of digital X-ray images that are produced in hospitals is increasing incredibly fast. Efficient storing, processing and retrieving of X-ray images have thus become an important research topic. With the exponential need that arises in the search for the clinically relevant and visually similar medical images over a vast database, the arena of digital imaging techniques is forced to provide a potential and path-breaking methodology in the midst of technical advancements so as to give the best match in accordance to the user’s query image. CBIR helps doctors to compare X-rays of their current patients with images from similar cases and they could also use these images as queries to find the similar entries in the X-ray database. This paper focuses on six different classes of X-ray images, viz. chest, skull, foot, spine, pelvic and palm for efficient image retrieval. Initially the various X-rays are automatically classified into the six-different classes using BPNN and SVM as classifiers and GLCM co-efficient as features for classification. Indexing is done to make the retrieval fast and retrieval of similar images is based on the city block distance.  
 
Publisher CIRWORLD
 
Date 2013-07-30
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
 
Format application/pdf
 
Identifier http://cirworld.com/index.php/ijct/article/view/3078ijct
 
Source INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY; Vol 12 No 7; 3742-3748
2277-3061
 
Language eng
 
Relation http://cirworld.com/index.php/ijct/article/view/3078ijct/2990
 
Rights Copyright (c) 2016 INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY
http://creativecommons.org/licenses/by/4.0
 

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