US 11,816,832 B2
Devices, systems, and methods for medical imaging
Qiulin Tang, Buffalo Grove, IL (US); Jian Zhou, Buffalo Grove, IL (US); and Zhou Yu, Glenview, IL (US)
Assigned to CANON MEDICAL SYSTEMS CORPORATION, Otawara (JP)
Filed by CANON MEDICAL SYSTEMS CORPORATION, Tochigi (JP)
Filed on Nov. 18, 2020, as Appl. No. 16/951,931.
Prior Publication US 2022/0156919 A1, May 19, 2022
Int. Cl. G06T 7/00 (2017.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01); G16H 50/70 (2018.01); G06N 3/08 (2023.01); G06T 7/12 (2017.01); G06T 11/00 (2006.01); A61B 6/03 (2006.01); A61B 6/00 (2006.01); G16H 50/50 (2018.01)
CPC G06T 7/0012 (2013.01) [A61B 6/032 (2013.01); A61B 6/504 (2013.01); A61B 6/5264 (2013.01); G06N 3/08 (2013.01); G06T 7/12 (2017.01); G06T 11/005 (2013.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01); G16H 50/50 (2018.01); G16H 50/70 (2018.01); G06T 2207/10081 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30101 (2013.01); G06T 2211/436 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method comprising:
obtaining scan data that were generated by scanning a scanned region,
wherein the scan data include groups of scan data,
wherein each group, of the groups of scan data, was captured at a respective angle, and
wherein each group's respective angle is different from every other group's respective angle;
performing a reconstruction process on a first subset of the groups of scan data, thereby generating a first partial reconstruction of at least part of the scanned region;
performing a reconstruction process on a second subset of the groups of scan data, thereby generating a second partial reconstruction of the at least part of the scanned region, wherein the first subset is different from the second subset;
inputting the first partial reconstruction and the second partial reconstruction into a machine-learning model, which generates one or more motion-compensated reconstructions of the at least part of the scanned region based at least on the first partial reconstruction and the second partial reconstruction;
calculating a respective edge entropy of each of the one or more motion-compensated reconstructions of the at least part of the scanned region; and
adjusting the machine-learning model based on the respective edge entropy of each of the one or more motion-compensated reconstructions.