Self-supervised reconstruction framework via motion- and physics-informed learning for four-dimensional magnetic resonance fingerprinting
SS-4DMRF is proposed, the first self-supervised reconstruction framework for 4DMRF, to reconstruct motion-resolved tissue maps without using supervised image labels and advances the precision of liver cancer radiotherapy and establishes a clinically feasible platform for abdominal quantitative MRI in oncology.