US 12,282,856 B2
Systems and methods for magnetic resonance imaging standardization using deep learning
Tao Zhang, Mountain View, CA (US); Enhao Gong, Sunnyvale, CA (US); and Gregory Zaharchuk, Stanford, CA (US)
Assigned to SUBTLE MEDICAL, INC., Menlo Park, CA (US)
Filed by Subtle Medical, Inc., Menlo Park, CA (US)
Filed on Nov. 23, 2022, as Appl. No. 18/058,658.
Application 18/058,658 is a continuation of application No. 17/097,436, filed on Nov. 13, 2020, granted, now 11,550,011.
Application 17/097,436 is a continuation of application No. PCT/US2019/037235, filed on Jun. 14, 2019.
Claims priority of provisional application 62/685,774, filed on Jun. 15, 2018.
Prior Publication US 2023/0162043 A1, May 25, 2023
Int. Cl. G06N 3/088 (2023.01); G01R 33/54 (2006.01); G06N 3/04 (2023.01); G06T 7/00 (2017.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01)
CPC G06N 3/088 (2013.01) [G01R 33/54 (2013.01); G06N 3/04 (2013.01); G06T 7/0012 (2013.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06T 2207/10088 (2013.01); G06T 2207/20081 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method for standardizing medical imaging, the method comprising:
acquiring one or more input images using one or more imaging devices, wherein the one or more imaging devices are of a same imaging modality and the one or more imaging devices correspond to one or more different image styles;
determining a standardized image style for processing the one or more input images;
predicting a synthesized output image by processing the one or more input images using a deep network model, wherein the synthesized output image has the standardized image style; and
displaying the synthesized output image with the standardized image style on a display device.