US 12,272,023 B2
Deep learning multi-planar reformatting of medical images
Bipul Das, Chennai (IN); Rakesh Mullick, Bangalore (IN); Deepa Anand, Bangalore (IN); Sandeep Dutta, Celebration, FL (US); Uday Damodar Patil, Bangalore (IN); and Maud Bonnard, Brookfield, WI (US)
Assigned to GE Precision Healthcare LLC, Wauwatosa, WI (US)
Filed by GE Precision Healthcare LLC, Wauwatosa, WI (US)
Filed on Mar. 15, 2022, as Appl. No. 17/654,864.
Prior Publication US 2023/0298136 A1, Sep. 21, 2023
Int. Cl. G06T 3/60 (2024.01); G06T 7/73 (2017.01); G06V 10/774 (2022.01); G06V 10/82 (2022.01); G16H 50/20 (2018.01)
CPC G06T 3/60 (2013.01) [G06T 7/73 (2017.01); G06V 10/774 (2022.01); G06V 10/82 (2022.01); G16H 50/20 (2018.01); G06T 2200/04 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06V 2201/031 (2022.01)] 16 Claims
OG exemplary drawing
 
1. A system, comprising:
a processor that executes computer-executable components stored in a computer-readable memory, the computer-executable components comprising:
a receiver component that accesses a three-dimensional medical image;
a detection component that localizes, via execution of a machine learning model, a set of landmarks depicted in the three-dimensional medical image, a set of principal anatomical planes depicted in the three-dimensional medical image, and a set of organs depicted in the three-dimensional medical image; and
an orientation component that determines an anatomical orientation exhibited by the three-dimensional medical image, based on the set of landmarks, the set of principal anatomical planes, or the set of organs.