A proposed quantitative approach to classify brain MRI

Madhulika Bhatia (), Abhay Bansal and Divakar Yadav
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Madhulika Bhatia: Amity University
Abhay Bansal: Amity University
Divakar Yadav: Jaypee University

International Journal of System Assurance Engineering and Management, 2017, vol. 8, issue 2, No 3, 577-584

Abstract: Abstract Analysis of magnetic resonance images of brain is done statistically using t test in excel and SPSS. The methodology would help the medical specialists to mechanize the examination of MRI’s of brain to differentiate the tumor from non tumor pictures to upgrade the therapeutic medical considerations. Tumor brain images can be classified from non tumor brain MRI images using a novel approach which detect grey matter in MRI images. The basic images preprocessing steps are followed like displaying of grey matter, segmentation, grey matter extraction and all is executed in Matlab environment. Statistical technique like t test in excel and SPSS is performed for classification of brain MRI images on the basis of grey matter extracted is done using Matlab. Our novel approach uses the benefits of existing preprocessing methods and filters available in Matlab for effectual extraction and analysis of brain MRI images. The work has been tested on 50 variables on forty-six subjects. Out of forty-six, twenty-four belong to healthy group and rest twenty-two belong to unhealthy. The work is assessed using t test in SPSS. The brain images are taken from the BRAINIX database and neuroimaging data repository. The proposed algorithm will be an easy approach for doctors and physicians to provide easy option for medical image analysis.

Keywords: Magnetic resonance imaging; Image processing; Medical images; Statistics; t test (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s13198-016-0465-8

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