A Novel Approach for MRI Brain Images Segmentation

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Author(s)

Abo-Eleneen Z. A 1,2,* Gamil Abdel-Azim 1,3

1. College of Scince, Qassim University, Saudi Arabia.

2. College of Computer& Informatics, Zagazig University, Egypt.

3. College of Computer& Informatics, Canal Suez University, Egypt.

* Corresponding author.

DOI: https://doi.org/10.5815/ijigsp.2013.03.02

Received: 8 Nov. 2012 / Revised: 15 Dec. 2012 / Accepted: 22 Jan. 2013 / Published: 8 Mar. 2013

Index Terms

Thresholding, Magnetic resonance images, Medical image, Histogram, Fisher information measure, Entropy

Abstract

Segmentation of brain from magnetic resonance (MR) images has important applications in neuroimaging, in particular it facilitates in extracting different brain tissues such as cerebrospinal fluids, white matter and gray matter. That helps in determining the volume of the tissues in three-dimensional brain MR images, which yields in analyzing many neural disorders such as epilepsy and Alzheimer disease. The Fisher information is a measure of the fluctuations in the observations. In a sense, the Fisher information of an image specifies the quality of the image. In this paper, we developed a new thresholding method using the Fisher information measure and intensity contrast to segment medical images. It is the weighted sum of the Fisher information measure and intensity contrast between the object and background. This technique is a powerful method for noisy image segmentation. The method applied on a normal MR brain images and a glioma MR brain images. Experimental results show that the use of the Fisher information effectively segmented MR brain images.

Cite This Paper

Abo-Eleneen Z. A, Gamil Abdel-Azim,"A Novel Approach for MRI Brain Images Segmentation", IJIGSP, vol.5, no.3, pp.10-18, 2013. DOI: 10.5815/ijigsp.2013.03.02 

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