Brain MRI

Brain MRI research focuses on improving image acquisition, analysis, and application through advanced computational methods. Current efforts concentrate on developing novel deep learning architectures, such as diffusion models and transformers, for tasks including faster reconstruction, anomaly detection (e.g., tumor identification, lesion segmentation), and harmonization of multi-site data. These advancements enhance diagnostic accuracy, enable more efficient workflows, and facilitate large-scale studies by addressing challenges like data scarcity, image quality variability, and inter-site differences in acquisition protocols. Ultimately, these improvements promise to significantly impact clinical practice and neuroimaging research.