US 12,106,402 B2
Architecture for artificial intelligence-based magnetic resonance reconstruction
Nirmal Janardhanan, Monmouth Junction, NJ (US); Laszlo Lazar, Gheorgheni (RO); Boris Mailhe, Plainsboro, NJ (US); Simon Arberet, Princeton, NJ (US); Mariappan S. Nadar, Plainsboro, NJ (US); Dorin Comaniciu, Princeton, NJ (US); Kelvin Chow, Chicago, IL (US); and Michael Bush, Brooklyn, NY (US)
Assigned to Siemens Healthineers AG, Forchheim (DE)
Filed by Siemens Healthineers AG, Forchheim (DE)
Filed on Oct. 6, 2021, as Appl. No. 17/450,075.
Prior Publication US 2023/0108663 A1, Apr. 6, 2023
Int. Cl. G06T 11/00 (2006.01); G01R 33/48 (2006.01); G06T 7/00 (2017.01)
CPC G06T 11/005 (2013.01) [G01R 33/4818 (2013.01); G06T 7/0012 (2013.01); G06T 2207/10088 (2013.01)] 18 Claims
OG exemplary drawing
 
1. A system for magnetic resonance (MR) reconstruction in medical imaging, the system comprising:
an MR scanner configured to scan a region of a patient, the scan providing k-space data;
a scanner processor of the MR scanner, the scanner processor configured to extract the k-space data from an imaging processing of the MR scanner, the scanner processor configured to format the k-space data for transmission over a computer network;
a server remote from the MR scanner, the server communicatively connected to the scanner processor by the computer network, the server configured to reconstruct a representation from the k-space data with a reconstruction using a first machine-learned model selected from a library, wherein the scanner processor is configured to receive the representation and inject the received representation into the imaging process; and
a display of the MR scanner configured to display an image from the representation.