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:
Jun. 28, 2022

Filed:

Feb. 27, 2020
Applicant:

Hitachi, Ltd., Tokyo, JP;

Inventors:

Masahiro Ogino, Tokyo, JP;

Yukio Kaneko, Tokyo, JP;

Zisheng Li, Tokyo, JP;

Yoshihisa Sotome, Tokyo, JP;

Assignee:

HITACHI, LTD., Tokyo, JP;

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06T 7/00 (2017.01); A61B 6/00 (2006.01); A61B 5/055 (2006.01);
U.S. Cl.
CPC ...
G06T 7/0012 (2013.01); A61B 5/055 (2013.01); A61B 6/469 (2013.01); A61B 6/5217 (2013.01); G06T 2207/10116 (2013.01); G06T 2207/30096 (2013.01);
Abstract

An image diagnostic device that obtains a prediction model indicating a higher accuracy diagnosis prediction result includes: an observation unit that collects an image of an examination object; and an image processing unit that generates first image data from the image, and performs image processing of the first image data. The image processing unit is provided with: a feature extraction unit that extracts a first feature from the first image data; a feature transformation unit that converts the first feature to a second feature to be extracted from second image data; and an identification unit that calculates a prescribed parameter value using the converted second feature. The feature extraction unit includes a prediction model learned using a plurality of combinations of the first image data and feature, and the feature transformation unit includes a feature transformation model learned using a plurality of combinations of the first and second features.


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