US 12,078,706 B2
Techniques for determining a functional magnetic resonance data set
Julian Richter, Unterpleichfeld (DE); and Manuel Stich, Parkstein (DE)
Assigned to Siemens Healthineers AG, Erlangen (DE)
Filed by Siemens Healthcare GmbH, Erlangen (DE)
Filed on Sep. 16, 2022, as Appl. No. 17/946,387.
Claims priority of application No. 21197324 (EP), filed on Sep. 17, 2021.
Prior Publication US 2023/0089051 A1, Mar. 23, 2023
Int. Cl. G01V 3/00 (2006.01); G01R 33/48 (2006.01); G01R 33/561 (2006.01); G01R 33/565 (2006.01)
CPC G01R 33/5611 (2013.01) [G01R 33/4818 (2013.01); G01R 33/56509 (2013.01)] 18 Claims
OG exemplary drawing
 
1. A method for determining a functional magnetic resonance (MR) data set of an imaging region of a brain of a patient, the method comprising:
acquiring, via control device circuitry using a plurality of reception coils as part of blood oxygenation level dependent (BOLD) functional MR imaging, (i) MR signals using parallel imaging, and (ii) a MR sequence defining a k-space trajectory in which undersampling in at least two k-space directions is performed;
reconstructing, via the control device circuitry using a reconstruction technique for undersampled MR data, the functional MR data set from (i) the MR signals, and (ii) sensitivity information regarding the plurality of reception coils; and
generating, via the control device circuitry, MR images of the imaging region of the brain of the patient based upon the functional MR data set,
wherein the k-space trajectory is selected to enable a controlled aliasing in each one of three spatial dimensions, including a readout direction, and
wherein reconstructing the functional MR data set comprises using a low rank plus sparse reconstruction technique in which dynamic MR data as a space-time matrix is used as a linear superposition of a spatially- and temporally-correlated image background matrix and a sparse dynamic information matrix.