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Feature Evaluation and Classification for Content-Based Medical Image Retrieval System

Feature Evaluation and Classification for Content-Based Medical Image Retrieval System
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Author(s): Ivica Dimitrovski (Ss. Cyril and Methodius University in Skopje, Macedonia) and Suzana Loskovska (Ss. Cyril and Methodius University in Skopje, Macedonia)
Copyright: 2010
Pages: 23
Source title: Ubiquitous Health and Medical Informatics: The Ubiquity 2.0 Trend and Beyond
Source Author(s)/Editor(s): Sabah Mohammed (Lakehead University, Canada) and Jinan Fiaidhi (Lakehead University, Canada)
DOI: 10.4018/978-1-61520-777-0.ch024

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Abstract

Image retrieval in general and content-based image retrieval (CBIR) in particular are well-known research fields in information management. A large number of methods have been proposed and investigated in both areas but satisfactory general solution has not still been developed. The aim of this research is to develop highly flexible web-based system for storage, organization and retrieval of medical images. The system besides text and metadata retrieval also supports querying by image to find visually similar images to presented query. Several algorithms and techniques were implemented in the system to support content-based retrieval. For efficient and reliable search machine learning techniques were included in the system.

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