MR image analysis of neonatal brain using adaptive mathematical morphological processing and region based segmentation

Abstract

In the study of evaluation of infant brain development, the segmentation of obtained MR images is an important step. When compared with the MR images of adult brain it is difficult to identify the different regions in infant brains with that of the methods used for the analysis of adult brains. This is due to the size difference of the brain and the differences in the properties of the brain tissues. So, for analyzing these MR images it requires manual interaction with the images resulting in the bias of the results. For this problem we propose another approach for the segmentation of neonatal brain MR images. This method doesn’t require any manual interaction and produces unbiased results. Our algorithm segments the different layers (right hemisphere, left hemisphere, cerebellum, brain stem) and the different tissues like sub cortical gray matter, Militated & un mylinated gray matter and cerebrospinal fluid, resulting in the better understanding of the development of different parts of the brain. Our algorithm can be used for the analysis of MR images of infant brains of age as less as 3to6 months.