US 12,189,013 B2
Magnetic resonance imaging with a dynamic diffusion-weighting
Mario Zeller, Erlangen (DE); and Adam Kettinger, Erlangen (DE)
Assigned to Siemens Healthineers AG, Erlangen (DE)
Filed by Siemens Healthcare GmbH, Erlangen (DE)
Filed on Sep. 22, 2022, as Appl. No. 17/950,980.
Claims priority of application No. 21198721 (EP), filed on Sep. 24, 2021.
Prior Publication US 2023/0098417 A1, Mar. 30, 2023
Int. Cl. A61B 5/0205 (2006.01); A61B 5/055 (2006.01); G01R 33/48 (2006.01); G01R 33/563 (2006.01); G06N 3/08 (2023.01)
CPC G01R 33/56341 (2013.01) [A61B 5/0205 (2013.01); A61B 5/055 (2013.01); G01R 33/4818 (2013.01); G06N 3/08 (2013.01)] 15 Claims
OG exemplary drawing
 
1. A method for diffusion-weighted magnetic resonance (MR) imaging of an object, which undergoes a cyclic motion, comprising:
determining a first sub-period type of the cyclic motion for a first acquisition timeframe, wherein the first sub-period type corresponds to one of two or more predefined characteristic types of sub-periods of the cyclic motion;
selecting a first amount of diffusion-weighting based on the first sub-period type;
performing a first MR-acquisition during the first acquisition timeframe, wherein a diffusion-weighting according to the first amount of diffusion-weighting is applied; and
generating an MR-image representing the object based on MR-data including a first MR-dataset obtained as a result of the first MR-acquisition.
 
14. A non-transitory computer-readable storage medium with an executable program stored thereon, that when executed, instructs a processor to perform a method for diffusion-weighted magnetic resonance (MR) imaging of an object, which undergoes a cyclic motion, comprising:
determining a first sub-period type of the cyclic motion for a first acquisition timeframe, wherein the first sub-period type corresponds to one of two or more predefined characteristic types of sub-periods of the cyclic motion;
selecting a first amount of diffusion-weighting based on the first sub-period type;
performing a first MR-acquisition during the first acquisition timeframe, wherein a diffusion-weighting according to the first amount of diffusion-weighting is applied; and
generating an MR-image representing the object based on MR-data including a first MR-dataset obtained as a result of the first MR-acquisition.