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:
Oct. 08, 2024

Filed:

Nov. 19, 2019
Applicant:

Koninklijke Philips N.v., Eindhoven, NL;

Inventors:

Karsten Sommer, Hamburg, DE;

Michael Gunter Helle, Hamburg, DE;

Assignee:

Koninklijke Philips N.V., Eindhoven, NL;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G01R 33/54 (2006.01); G01R 33/56 (2006.01); G01R 33/563 (2006.01); G06N 3/045 (2023.01); G06N 3/084 (2023.01); G06T 7/00 (2017.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01);
U.S. Cl.
CPC ...
G01R 33/543 (2013.01); G01R 33/546 (2013.01); G01R 33/5608 (2013.01); G01R 33/56308 (2013.01); G01R 33/56366 (2013.01); G06T 7/0012 (2013.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06T 2207/10096 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/20101 (2013.01); G06T 2207/30016 (2013.01);
Abstract

The invention provides for a method of training a neural network () configured for providing a further processing location (). The method comprises providing () a labeled medical image (), wherein the labeled medical image comprises multiple labels each indicating a truth processing location (). The method further comprises inputting () the labeled medical image into the neural network to obtain one trial processing location. The one trial processing location comprises a most likely trial processing location (). The method further comprises determine () the closest truth processing location () for the most likely trial processing location. The method further comprises calculating () an error vector () using the closest truth processing location and the most likely trial processing location. The method further comprises training () the neural network using the error vector.


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