US 11,776,173 B2
Generating reformatted views of a three-dimensional anatomy scan using deep-learning estimated scan prescription masks
Chitresh Bhushan, Glenville, NY (US); Dattesh Dayanand Shanbhag, Bengaluru (IN); and Rakesh Mullick, Bangalore (IN)
Assigned to GE PRECISION HEALTHCARE LLC, Wauwatosa, WI (US)
Filed by GE Precision Healthcare LLC, Milwaukee, WI (US)
Filed on May 4, 2021, as Appl. No. 17/307,517.
Prior Publication US 2022/0358692 A1, Nov. 10, 2022
Int. Cl. G06T 11/00 (2006.01); G06T 7/80 (2017.01); G06T 7/11 (2017.01); G06V 10/25 (2022.01); A61B 5/055 (2006.01); A61B 5/00 (2006.01); G06T 7/00 (2017.01)
CPC G06T 11/008 (2013.01) [A61B 5/055 (2013.01); A61B 5/742 (2013.01); G06T 7/0012 (2013.01); G06T 7/11 (2017.01); G06T 7/80 (2017.01); G06V 10/25 (2022.01); G06T 2207/10072 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/30016 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A system, comprising:
a memory that stores computer executable components; and
a processor that executes the computer executable components stored in the memory, wherein the computer executable components comprise:
a mask generation component that employs a pre-trained neural network model to generate masks for different anatomical landmarks depicted in one or more calibration images captured of an anatomical region of a patient; and
a reformatting component that reformats three-dimensional image data captured of the anatomical region of the patient using the masks to generate different representations of the three-dimensional image data that correspond to the different anatomical landmarks, wherein the different representations comprise at least one of synthetic two-dimensional images generated from the three-dimensional image data or synthetic three-dimensional images generated from the three-dimensional image data.