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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.

Patent No.:

US 11842808 B1

PDFFull Text
Date of Patent:
Dec. 12, 2023

Filed:

Sep. 30, 2020

Ultrasound diagnostic imaging training apparatus, ultrasound diagnostic imaging apparatus, identification model training method, non-transitory recording medium storing computer readable training program, and ultrasound diagnostic apparatus

Applicant:

Konica Minolta, Inc., Tokyo, JP;

Inventor:

Yoshihiro Takeda, Tokyo, JP;

Assignee:

KONICA MINOLTA, INC., Tokyo, JP;

Attorney:

LUCAS & MERCANTI, LLP

Primary Examiner:

Mohammed Rachedine

Int. Cl.
CPC ...
A61B 8/08 (2006.01); A61B 8/14 (2006.01); A61B 8/00 (2006.01); G06F 18/214 (2023.01); G06F 18/28 (2023.01); G06F 18/40 (2023.01); G06N 20/00 (2019.01); G06V 10/22 (2022.01); G16H 30/40 (2018.01); G16H 30/20 (2018.01); G06V 10/56 (2022.01); G06V 10/764 (2022.01); G06V 10/772 (2022.01); G06V 10/774 (2022.01);
U.S. Cl.
CPC ...
G16H 30/40 (2018.01); A61B 8/085 (2013.01); A61B 8/0841 (2013.01); A61B 8/14 (2013.01); A61B 8/463 (2013.01); A61B 8/469 (2013.01); G06F 18/214 (2023.01); G06F 18/28 (2023.01); G06F 18/40 (2023.01); G06N 20/00 (2019.01); G06V 10/235 (2022.01); G06V 10/56 (2022.01); G06V 10/764 (2022.01); G06V 10/772 (2022.01); G06V 10/774 (2022.01); G16H 30/20 (2018.01); G06V 2201/03 (2022.01);
Abstract

An ultrasound diagnostic imaging training apparatus for training an identification model to be used for identifying a target in an ultrasound image generated based on reflected ultrasound reflected from inside a subject includes a first hardware processor that extracts a first image from the ultrasound image used for training and generates teacher data in which a feature value of a second image included in the first image is associated with information relating to a likelihood of the target, the generation of the teacher data being based on the first image and preset reference data; and a second hardware processor that trains the identification model through machine learning using the teacher data.

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