International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Content-Based Lung Image Categorization by Metric Learning for Interstitial Lung Diseases

Author : Geethu Gopal . G ¹

Date of Publication :7th September 2016

Abstract: Content Based Image Retrieval (CBIR) systems retrieve lung images from that database which are similar to the query image. CBIR is the application of computer vision. That has been one on the most vivid research areas in the field of computer vision over the last 10 years. Instead of text based searching, CBIR efficiently retrieves images that are visually similar to query image. In CBIR query is given in the form of image. This paper aims to provide an efficient medical image data Retrieval in Lung Diseases. Finding similar images or reference is one way to assist radiologist for differential diagnosis of Interstitial Lung Diseases (ILDs). Content Based Image Retrieval (CBIR) has been identified as an important research topic in this direction. This motivated us to design a special purpose CBIR system (Med-IR) for Interstitial Lung Diseases (ILDs), where the user can provide one interstitial disease pattern as input and the system will retrieve few most similar patterns available in the database. CBIR is an effective technique, which is appropriate for large-scale indexing, is adopted, extended and integrated to the proposed framework so as to achieve optimized search and retrieval of rich media content even from large database.

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