US 11,941,738 B2
Systems and methods for personalized patient body modeling
Srikrishna Karanam, Brighton, MA (US); Meng Zheng, Cambridge, MA (US); and Ziyan Wu, Lexington, MA (US)
Assigned to Shanghai United Imaging Intelligence Co., Ltd., Shanghai (CN)
Filed by Shanghai United Imaging Intelligence Co., Ltd., Shanghai (CN)
Filed on Oct. 28, 2021, as Appl. No. 17/513,392.
Prior Publication US 2023/0132479 A1, May 4, 2023
Int. Cl. G06T 13/40 (2011.01); G06T 17/20 (2006.01); G06T 19/20 (2011.01)
CPC G06T 13/40 (2013.01) [G06T 17/20 (2013.01); G06T 19/20 (2013.01); G06T 2210/41 (2013.01); G06T 2219/2004 (2013.01)] 16 Claims
OG exemplary drawing
 
1. A method for obtaining a personalized human model, the method comprising:
obtaining a three-dimensional (3D) model of a person, wherein the 3D model is generated using one or more neural networks based on one or more images of the person and wherein the one or more neural networks are pre-trained to generate the 3D model;
obtaining the one or more images of the person;
determining, independently from the 3D model generated using the one or more neural networks, at least one of a first set of key body locations of the person or a first body shape of the person based on the one or more images of the person;
determining at least one of a second set of key body locations of the person or a second body shape of the person based on the 3D model generated using the one or more neural networks; and
adjusting the 3D model of the person by minimizing at least one of a first Euclidean distance between the first set of key body locations of the person and the second set of key body locations of the person, or a second Euclidean distance between the first body shape of the person and the second body shape of the person.