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:
Mar. 05, 2024

Filed:

Apr. 06, 2021
Applicant:

Canon Kabushiki Kaisha, Tokyo, JP;

Inventors:

Yoshihiko Iwase, Kanagawa, JP;

Manabu Yamazoe, Tokyo, JP;

Hideaki Mizobe, Kanagawa, JP;

Hiroki Uchida, Tokyo, JP;

Ritsuya Tomita, Kanagawa, JP;

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/20 (2017.01); A61B 3/00 (2006.01); A61B 3/10 (2006.01); A61B 3/12 (2006.01); G06F 18/214 (2023.01); G06N 20/00 (2019.01); G06T 5/00 (2006.01); G06T 7/00 (2017.01); G06V 10/75 (2022.01); G06V 40/18 (2022.01); H04N 23/698 (2023.01); G06V 40/14 (2022.01);
U.S. Cl.
CPC ...
G06T 5/002 (2013.01); A61B 3/0025 (2013.01); A61B 3/0041 (2013.01); A61B 3/102 (2013.01); A61B 3/1241 (2013.01); G06F 18/214 (2023.01); G06N 20/00 (2019.01); G06T 5/007 (2013.01); G06T 7/0012 (2013.01); G06T 7/20 (2013.01); G06V 10/75 (2022.01); G06V 40/193 (2022.01); H04N 23/698 (2023.01); G06T 2207/10101 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/30041 (2013.01); G06T 2207/30168 (2013.01); G06V 40/14 (2022.01);
Abstract

A medical image processing apparatus includes: an obtaining unit configured to obtain a first image that is a motion contrast en-face image of an eye to be examined; and an image quality improving unit configured to generate a second image with at least one of lower noise and higher contrast than the obtained first image using the obtained first image as input data that is input into an image quality improving engine, wherein the image quality improving engine includes a machine learning engine that has been obtained by using training data including a second image with at least one of lower noise and higher contrast than a first image that is a motion contrast en-face image of an eye to be examined.


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