Objectives: Every year millions of babies born preterm and it is a serious issue in developed countries. Preterm birth is worldwide problem of young children. Methods/Statistical analysis: Advances in Magnetic Resonance Imaging (MRI), comprehensive images of the newborn brain is visualized non-invasively. Here we are focusing on the early assessment of brain development in neonates and premature infants using multi stage segmentation and classification approach with quantitative analysis. To

more »

... ieve higher segmentation and classification accuracy neural network classifier are used. It is also helpful in detection and classification of more number of brain tissues. Findings: The accurate segmentation and classification of brain tissues is very much useful in evaluating the brain development of newborn and premature infants. Therefore, newborn brain MRI forms a crucial part in analytical neuro-imaging; principally in the neonatal stage. Our method gives higher dice similarity index values and higher computational speed as compared to existing methods. Application: Resulting segmentations are used for volumetric analysis and quantification of cortical descriptions. This analysis plays vital role for neonatologists in early detection and diagnosis of neural impairments.