Magnetic resonance imaging (MRI) relies on radiofrequency (RF) excitation of proton spin. Clinical diagnosis requires a comprehensive collation of biophysical data via multiple MRI contrasts, acquired using a series of RF sequences that lead to lengthy examinations. Here, we developed a vision transformer-based framework that explicitly utilizes RF excitation information alongside per-subject calibration data (acquired within 28.2 s), to generate a wide variety of image contrasts including fully quantitative molecular, water relaxation, and magnetic field maps. The method was validated across healthy subjects and a cancer patient in two different imaging sites, and proved to be 94% faster than alternative protocols. The transformer-based MRI framework (TBMF) may support the efforts to reveal the molecular composition of the human brain tissue in a wide range of pathologies, while offering clinically attractive scan times.
© 2025. The Author(s).