| CPC G06T 7/0012 (2013.01) [A61B 34/20 (2016.02); G06T 3/10 (2024.01); G06T 7/55 (2017.01); G06T 7/73 (2017.01); G06T 17/20 (2013.01); G06V 10/26 (2022.01); A61B 2034/2055 (2016.02); G06T 2207/10081 (2013.01); G06T 2207/10088 (2013.01); G06T 2207/10116 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01)] | 7 Claims |

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1. A method of generating a medical image, the method comprising:
obtaining a first two-dimensional image of an anatomical object;
extracting first information associated with the anatomical object from the first image;
obtaining a second two-dimensional image of the anatomical object;
extracting second information associated with the anatomical object from the second image;
generating the medical image based on the first information, the second information, and predetermined information that is associated with images of anatomical objects of a type that is a type of the anatomical object; and
generating a three-dimensional model of the anatomical object based on the medical image generating third information associated with the anatomical object based on the first information and the second information,
providing the interpolated image to a robotic surgery system, the robotic surgery system then using the interpolate image to actuate a robotic arm to perform a surgical procedure,
wherein generating the medical image includes generating the medical image based on the third information and the predetermined information
wherein the predetermined information includes a globally-optimized style vector,
wherein extracting the first information includes generating a first content vector based on the first image,
wherein extracting the second information includes generating a second content vector based on the second image,
wherein generating the third information includes generating a third content vector based on the first content vector and the second content vector, and
wherein generating the medical image includes interpolating the medical image using the third content vector and the globally-optimized style vector,
wherein the generating the medical image includes using neural networks to identify features and contrast in 3D voxels.
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