BME Seminar by Prof. Dafna Ben Bashat

Clinical MRI provides rich structural and physiological information, yet much of its quantitative potential remains underutilized. This talk presents an engineering framework for developing and translating quantitative MRI tools that integrate advanced MRI methods, physics-based modeling, algorithm design, and machine learning to generate robust and reproducible imaging biomarkers.

The work focuses on multiparametric imaging of tissue microstructure, perfusion, vascular function, and metabolism, using real-world clinical data within a hospital environment. Methods are designed for robustness, quantitative reliability, and integration into routine clinical workflows. Applications in brain tumors, cerebrovascular disease, and fetal MRI demonstrate how advanced MRI combined with clinically grounded engineering enables the translation of methodological innovation into practical clinical impact.