Analysing Fetal Brain Development using Deep Learning Techniques

Fetal brain development is a critical indicator of the health and growth of the fetus, and accurate gestational age prediction can aid in monitoring fetal health. In order to predict gestational age from fetal brain MRI data, this study proposes a deep learning-based method utilising a Convolutional Neural Network (CNN). According to the gestational age, the model divides foetal brain development into three groups: small, medium, and giant. The input data is MRI scans, and high-quality training data is ensured by preprocessing procedures such skull stripping, intensity normalization, and data augmentation.A CNN model is created as part of the suggested process in order to automatically extract pertinent features from the MRI images. To classify the photos into the proper gestational age categories, the model uses a softmax output layer after several convolutional layers, pooling, and fully connected layers.