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BY-NC-ND 3.0 license Open Access Published by De Gruyter Open Access September 25, 2013

Efficient computer aided diagnosis of abnormal parts detection in magnetic resonance images using hybrid abnormality detection algorithm

C. Lakshmi Devasena EMAIL logo and M. Hemalatha
From the journal Open Computer Science

Abstract

In Medical Diagnosis, Magnetic Resonance Image (MRI) plays a momentous role. MRI is based on the physical and chemical principles of Nuclear Magnetic Resonance (NMR), a technique used to gain information about the nature of molecules. Retrieving a high quality MR Image for a medical diagnosis is critical. So denoising of Magnetic Resonance (MR) images and making them easy for human understanding form is a challenge. This research work presents an efficient Hybrid Abnormal Detection Algorithm (HADA) to detect the abnormalities in any part of the human body by MRIs. The proposed technique includes five stages: Noise Reduction, Smoothing, Feature Extraction, Feature Reduction and Classification. The proposed algorithm has been implemented and Classification accuracy of 98.80% has been achieved. The result shows that the proposed technique is robust and effective compared to other recent works. The system developed using the proposed algorithm will be a good computer aided diagnosis and decision making system in healthcare.

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Published Online: 2013-9-25
Published in Print: 2013-9-1

© 2013 Versita Warsaw

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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