An Examination of Methodological Approaches for Segmentating Fetal Brain MRI Images – Analysis

In today’s world and in the country like India, Women’s health needs more care. Especially the women’s health during the pregnancy period plays a vital role in both the mother as well as the baby’s care. As per a survey, among thousands three of them found to have fetal brain abnormalities. If these abnormalities are predicted at the early stage, then it will be an added advantage in saving both the life of mother and baby. During the pregnancy number of tests have to be performed to monitor fetal development. Tests like fetal ultrasound, Chorionic Villus Sampling, Amniocentesis, Fetal Echocardiogram, Fetal MRI imaging SCAN etc. The fetal brain abnormality can be predicted as well as treated at the early stage by analyzing the fetal brain MRI during the gestational period. Identifying abnormalities in fetal brain MRI images involves several essential steps, including image segmentation, analyzing images involves extracting distinctive features, refining their quality, identifying relevant patterns, and categorizing them based on specific criteria. The process of classification determines whether an abnormality is present or not. Analyzing images presents a complex undertaking owing to the diversity in shapes, spatial arrangements, and intensity levels within the images. This paper focuses on reviewing and comparing various segmentation techniques, highlighting their respective strengths and weaknesses.