Automatic segmentation of brain MRI of newborn and premature infants using neural network

Abstract

This paper focuses on the development of an accurate neonatal brain MRI segmentation algorithm and its clinical application to characterize normal brain development and investigate the neuro anatomical correlates of cognitive impairments. Neonatal brain segmentation is more challenging field because of anatomical variation and rapid brain development in the neonatal period. Segmentation of neonatal brain MR images is a fundamental process in the study and assessment of newborn brain development. Adult brain MRI segmentation techniques are not suitable for neonatal brain, because of substantial contrasts in tissue and structure properties between neonatal and adult brains. In this paper, we proposed an atlas free model to segment the newborn brain MRI images, using neural network approach. The segmentation of the neonatal brain in MR Imaging is a prerequisite to obtain quantitative measurements of regional brain structures.