Effective SWI-based brain segmentation method in an MR image

Abstract

Object recognition is usually processed based on region segmentation algorithm. Region segmentation in the IT field is carried out by computerized processing of various input information such as brightness, shape, and pattern analysis. If the information mentioned does not make sense, however, many limitations could occur with region segmentation during computer processing. Therefore, this paper suggests effective region segmentation method based on Susceptibility Weighted Imaging (SWI) within the magnetic resonance (MR) theory. In this study, the experiment had been conducted using images including the brain region and by getting up contrast enhancement image of SWI for texture analysis to enable region (white matter) segmentation even when the border line was not clear. As a result, an average area difference of 7.6%, which was higher than the accuracy of conventional region segmentation algorithm, was obtained.