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ISSN: 2168-9679

Journal of Applied & Computational Mathematics
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Review Article

Volume Estimation of Various Brain Components Using MR Images - A Technical Report

Fuhua Chen* and Katherine Hastings

West Liberty University, West Virginia, USA

*Corresponding Author:
Fuhua Chen
West Liberty University
West Virginia, USA
Tel: 3043365000
E-mail: [email protected]

Received Date: December 24, 2014; Accepted Date: February 27, 2015; Published Date: March 10, 2015

Citation: Chen F, Hastings K (2015) Volume Estimation of Various Brain Components Using MR Images - A Technical Report. J Appl Computat Math 4:207. doi: 10.4172/2168-9679.1000207

Copyright: © 2015 Chen F, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

In this paper, we present and discuss issues related to volume estimation of various brain components using MR brain images. We discuss pre-processing techniques to remove elements such as skull, blood vessels and fats from the MR images since these are non-essential to the volume calculations. The volume estimation is based on image segmentation. A challenge in MR brain image segmentation is to distinguish central gray matter from surrounding matters. This paper provides a frame work from pre-processing stage through volume estimation for white matter, gray matter and cerebrospinal fluid (CSF). The main contribution of this paper contains two parts. First, it provides a software-based method for interactive image pre-processing; second, it introduces a software-based, supervised interactive image segmentation method to deal with the segmentation of different matters, especially the central gray matter. Experiments with real data demonstrate the efficiency of our frame work.

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