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

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

Journal Title: INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY - Year 2014, Vol 12, Issue 7

Abstract

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 userâ€™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.Â Â

Authors and Affiliations

Sumathi Ganesan, T. S. Subashini

Keywords

Content based image retrieval back propagation neural network support vector machine gray level co-occurrence matrix and city block distance method

EP ID EP650506
DOI 10.24297/ijct.v12i7.3078
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