US 12,067,652 B2
Correction of magnetic resonance images using multiple magnetic resonance imaging system configurations
Christophe Michael Jean Schuelke, Hamburg (DE); Karsten Sommer, Hamburg (DE); George Randall Duensing, Hamburg (DE); and Peter Boernert, Hamburg (DE)
Assigned to Koninklijke Philips N.V., Eindhoven (NL)
Appl. No. 17/923,617
Filed by KONINKLIJKE PHILIPS N.V., Eindhoven (NL)
PCT Filed Apr. 21, 2021, PCT No. PCT/EP2021/060286
§ 371(c)(1), (2) Date Nov. 7, 2022,
PCT Pub. No. WO2021/228515, PCT Pub. Date Nov. 18, 2021.
Claims priority of provisional application 63/022,925, filed on May 11, 2020.
Claims priority of application No. 20176989 (EP), filed on May 28, 2020.
Prior Publication US 2023/0186532 A1, Jun. 15, 2023
Int. Cl. G06T 11/00 (2006.01); G01R 33/54 (2006.01); G01R 33/56 (2006.01); G01R 33/565 (2006.01)
CPC G06T 11/005 (2013.01) [G01R 33/543 (2013.01); G01R 33/5608 (2013.01); G01R 33/565 (2013.01); G06T 11/006 (2013.01); G06T 2211/424 (2013.01)] 15 Claims
OG exemplary drawing
 
1. A medical system comprising:
a memory storing machine executable instructions and access to an image generating neural network, wherein the image generating neural network is configured for outputting synthetic magnetic resonance image data in response to receiving reference magnetic resonance image data as input, wherein the image generating neural network is configured to generate the synthetic magnetic resonance image data as a simulation of magnetic resonance image data acquired according to a first configuration of a magnetic resonance imaging system when the reference magnetic resonance image data is acquired according to a second configuration of the magnetic resonance imaging system;
a computational system configured to control the medical system, wherein execution of the machine executable instructions causes the computational system to:
access measured k-space data acquired according to the first configuration of the magnetic resonance imaging system, wherein the measured k-space data is descriptive of a region of interest of a subject;
access the reference magnetic resonance image data, wherein the reference magnetic resonance image data is descriptive of the region of interest of the subject;
generate access to the synthetic magnetic resonance image data by inputting the reference magnetic resonance image data into the image generating neural network; and
arrange to reconstruct corrected magnetic resonance image data from the measured k-space data and the synthetic magnetic resonance image data.