US 11,682,135 B2
Systems and methods for detecting and correcting orientation of a medical image
Khaled Salem Younis, Parma Heights, OH (US); Katelyn Rose Nye, Waukesha, WI (US); Gireesha Chinthamani Rao, Pewaukee, WI (US); German Guillermo Vera Gonzalez, Menomonee Falls, WI (US); Gopal B. Avinash, San Ramon, CA (US); Ravi Soni, San Ramon, CA (US); Teri Lynn Fischer, Germantown, WI (US); and John Michael Sabol, Sussex, WI (US)
Assigned to GE PRECISION HEALTHCARE LLC, Milwaukee, WI (US)
Filed by GE Precision Healthcare, LLC, Milwaukee, WI (US)
Filed on Nov. 29, 2019, as Appl. No. 16/699,368.
Prior Publication US 2021/0166351 A1, Jun. 3, 2021
Int. Cl. G06T 3/60 (2006.01); G06T 7/73 (2017.01); G06T 7/00 (2017.01); G06N 3/08 (2023.01); G06N 3/04 (2023.01); G06F 18/214 (2023.01); G06V 10/764 (2022.01); G06V 10/774 (2022.01); G06V 10/44 (2022.01)
CPC G06T 7/73 (2017.01) [G06F 18/214 (2023.01); G06N 3/04 (2013.01); G06N 3/08 (2013.01); G06T 3/60 (2013.01); G06T 7/0012 (2013.01); G06V 10/454 (2022.01); G06V 10/764 (2022.01); G06V 10/774 (2022.01); G06T 2207/10116 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01)] 18 Claims
OG exemplary drawing
 
1. An x-ray image orientation detection and correction system, comprising:
a detection and correction computing device comprising at least one processor in communication with at least one memory device, wherein said at least one processor is programmed to:
execute a neural network model for analyzing x-ray images, wherein the neural network model is trained with training x-ray images as inputs and observed x-ray images associated with the training x-ray images as outputs, and the observed x-ray images are the training x-ray images adjusted to have a reference orientation;
receive an unclassified x-ray image;
analyze the unclassified x-ray image using the neural network model;
assign an orientation class to the unclassified x-ray image based on the analysis;
if the assigned orientation class is not the reference orientation, the at least one processor is programmed to:
adjust an orientation of the unclassified x-ray image using the neural network model, wherein the neural network model is configured to generate a corrected x-ray image based on the unclassified x-ray image; and
output the corrected x-ray image generated by the neural network model; and
if the assigned orientation class is the reference orientation, the at least one processor is programmed to output the unclassified x-ray image.