Abstract: The invention relates to a magnetic resonance imaging system, the magnetic resonance imaging system (100) comprising: —a memory (134, 136) storing machine executable instructions (160, 162, 164), pulse sequence commands (140) and a first machine learning model (146) comprising a first deep learning network (502), wherein the pulse sequence commands (140) are configured for controlling the magnetic resonance imaging system (100) to acquire a set of magnetic resonance imaging data, wherein the first machine learning model (146) comprises a first input and a first output, —a processor, wherein an execution of the machine executable instructions (160, 162, 164) causes the processor (130) to control the magnetic resonance imaging system (100) to repeatedly perform an acquisition and analysis process comprising: —acquiring a dataset (142.1, . . . , 142.

Abstract: The invention provides for a magnetic resonance imaging system (100) for acquiring magnetic resonance data (141) from an imaging zone (108). The magnetic resonance imaging system comprises a memory (134, 136) for storing machine executable instructions (150, 152, 154, 156) and pulse sequence commands (140). The pulse sequence commands cause the magnetic resonance imaging system to provide at least one spatially selective saturation pulse (408, 410) to at least one selected volume (124, 124?). The at least one selected volume is at least partially outside of a region of interest (123). The at least one selected volume is within the imaging zone. The region of interest is within the imaging zone, wherein the pulse sequence commands further cause the magnetic resonance imaging system to perform a non-selective inversion (412) of spins in the region of interest.