Diffusion Weighted

Diffusion-weighted imaging (DWI), a type of MRI, measures the diffusion of water molecules to reveal tissue microstructure and connectivity, primarily used to study brain white matter and detect lesions in various organs. Current research focuses on improving DWI data quality and analysis through deep learning techniques, including generative models for data augmentation and denoising, and novel network architectures like residual networks and multi-head encoders for improved segmentation and parameter estimation. These advancements enhance the accuracy and efficiency of DWI-based diagnostics and contribute to a deeper understanding of brain structure and disease processes, impacting fields like neurology, oncology, and fetal imaging.