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:
Feb. 15, 2022

Filed:

Dec. 12, 2019
Applicant:

Koninklijke Philips N.v., Eindhoven, NL;

Inventors:

Karsten Sommer, Hamburg, DE;

Sascha Krueger, Hamburg, DE;

Julian Senegas, Hamburg, DE;

Assignee:

Koninklijke Philips N.V., Eindhoven, NL;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/73 (2017.01); A61B 5/00 (2006.01); A61B 5/055 (2006.01);
U.S. Cl.
CPC ...
G06T 7/74 (2017.01); A61B 5/055 (2013.01); A61B 5/704 (2013.01); A61B 5/7267 (2013.01); A61B 5/742 (2013.01); A61B 5/7405 (2013.01); A61B 5/0035 (2013.01); A61B 5/0077 (2013.01); G06T 2207/20224 (2013.01);
Abstract

The invention provides for a medical instrument () comprising a medical imaging system () configured for acquiring medical imaging data () from a subject (); a subject support () configured for supporting the subject during acquisition of the medical imaging data; and an optical imaging system (') configured for acquiring optical imaging data () of the subject on the subject support. The execution of the machine executable instructions causes a processor () controlling the medical instrument to: control () the optical imaging system to acquire the optical imaging data; generate () the initial vector () using the optical imaging data; generate () the synthetic image by inputting the initial vector into a generator neural network; calculate () a difference () between the synthetic image and the optical imaging data; and provide () a warning signal () if the difference differs by a predetermined threshold. The generator neural network is trained to generate a synthetic image () of the subject on the subject support in response to inputting an initial vector.


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