The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Nov. 08, 2022

Filed:

Nov. 18, 2020
Applicant:

Canon Medical Systems Corporation, Otawara, JP;

Inventors:

James Sloan, Edinburgh, GB;

Owen Anderson, Edinburgh, GB;

Keith Goatman, Edinburgh, GB;

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 3/00 (2006.01); G06T 7/37 (2017.01); G06T 7/33 (2017.01); G06T 5/50 (2006.01); G06N 5/04 (2006.01); G06T 7/50 (2017.01); G16H 30/40 (2018.01); G06N 3/08 (2006.01); G06N 3/04 (2006.01);
U.S. Cl.
CPC ...
G06T 3/0068 (2013.01); G06N 3/0454 (2013.01); G06N 3/0472 (2013.01); G06N 3/08 (2013.01); G06N 5/04 (2013.01); G06T 5/50 (2013.01); G06T 7/337 (2017.01); G06T 7/37 (2017.01); G06T 7/50 (2017.01); G16H 30/40 (2018.01); G06T 2207/10081 (2013.01); G06T 2207/10088 (2013.01); G06T 2207/10104 (2013.01); G06T 2207/10108 (2013.01); G06T 2207/10116 (2013.01); G06T 2207/10132 (2013.01); G06T 2207/20081 (2013.01);
Abstract

An apparatus comprises processing circuitry configured to receive a plurality of training image data sets and a plurality of predetermined displacements. The processing circuitry is further configured to use the training image data sets and predetermined displacements to train a transformation regressor in combination with a discriminator in an adversarial fashion by repeatedly alternating a transformation regressor training process in which the transformation regressor is trained to predict displacements, and a discriminator training process in which the discriminator is trained to distinguish between predetermined displacements and displacements predicted by the transformation regressor.


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