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:
Sep. 05, 2023

Filed:

Apr. 13, 2021
Applicant:

Siemens Healthcare Gmbh, Erlangen, DE;

Inventors:

Siqi Liu, Princeton, NJ (US);

Yuemeng Li, Philadelphia, PA (US);

Arnaud Arindra Adiyoso, Nuremberg, DE;

Bogdan Georgescu, Princeton, NJ (US);

Sasa Grbic, Plainsboro, NJ (US);

Ziming Qiu, Brooklyn, NY (US);

Zhengyang Shen, Chapel Hill, NC (US);

Assignee:

SIEMENS HEALTHCARE GMBH, Erlangen, DE;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2022.01); G06T 7/00 (2017.01); G06T 7/62 (2017.01); G06V 10/25 (2022.01); G06V 10/82 (2022.01); G06V 10/44 (2022.01);
U.S. Cl.
CPC ...
G06T 7/0016 (2013.01); G06T 7/0014 (2013.01); G06T 7/62 (2017.01); G06V 10/25 (2022.01); G06V 10/454 (2022.01); G06V 10/82 (2022.01); G06T 2207/10116 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30096 (2013.01);
Abstract

A computer-implemented method is for classifying a lesion. In an embodiment, the method includes receiving a first medical image of an examination volume, the first medical image corresponding to a first examination time; receiving a second medical image of the examination volume, the second medical image corresponding to a second examination time, different from the first examination time; determining a first lesion area corresponding to a lesion within the first medical image; determining a registration function based on a comparison of the first medical image and the second medical image; determining a second lesion area within the second medical image based on the registration function and the first lesion area; and classifying the lesion within the first medical image based on the second lesion area. A computer-implemented method for providing a trained classification function, a classification system, and computer program products and computer-readable media are also disclosed.


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