AI-Enabled Segmentation of Brain MRI: Investigating Links Between Brain Attributes, Physical Activity, Cognitive Functions, and Genetics with Gender and Age Considerations.

The human brain has different parts which are responsible for different daily activities. White and grey matter form approximately 60% and 40% of our brains, respectively. Scientists have demonstrated that they undergo substantial changes throughout our lives. Magnetic Resonance Imaging (MRI), Diffusion MRI (dMRI), Functional MRI (fMRI), etc. techniques could be employed to map brain activities for different genders and ages. However, interpreting the data manually could lead to errors. We envisage incorporating Deep Learning (DL)/Machine Learning (ML) into the decision-making process regarding brain activities. This proposed project will investigate segmenting brain regions (e.g. white matter and grey matter) through Artificial Intelligence (AI) in predicting and diagnosing brain diseases, diagnostic accuracy, and contributing towards personalised medicine by co-relating brain parameters with physical activity, cognitive functions, and genetics.