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Analyzing Brain Microstructure Using Diffusion Weighted Imaging in Python

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  • Dhanushree
  • H P Mohan Kumar

Abstract

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.

Suggested Citation

  • Dhanushree & H P Mohan Kumar, 2025. "Analyzing Brain Microstructure Using Diffusion Weighted Imaging in Python," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 11(4), pages 378-384, August.
    • Handle: RePEc:jbh:ijsrcs:v11:y2025:i4:id:1648
    Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT25111670
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