Analyzing Brain Microstructure Using Diffusion Weighted Imaging in Python - Dhanushree M S; H P Mohan Kumar (International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2025)
Diffusion Weighted Imaging (DWI) is a sophisticated MRI technique that enables the visualization of water molecule movement within biological tissues, offering critical insights into the brain’s micro-structural integrity. This project focuses on implementing a Python based pipeline to analyze DWI data with the aim of detecting and classifying abnormalities such as strokes, tumors, and neuro degenerative diseases. Through data pre- processing, diffusion metric calculation (e.g., Fractional Anisotropy and Mean Diffusivity), and machine learni ng algorithms, the project facilitates accurate classification and visualization of brain regions. The use of open- source Python libraries and visualization tools allows for the creation of a robust, automated,and scalable framework for both clinical and research applications. The results provide improved diagnostic capabilities and a deeper understanding of brain connectivity, laying a foundation for further advancements in computational neuro imaging.