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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.

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