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. 10, 2023

Filed:

Sep. 06, 2022
Applicant:

Olympus Medical Systems Corp., Tokyo, JP;

Inventors:

Takashi Miyoshi, Kanagawa, JP;

Takuya Matsunaga, Tokyo, JP;

Kazuhito Horiuchi, Tokyo, JP;

Munenori Fukunishi, Tokyo, JP;

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G03B 13/36 (2021.01); H04N 23/67 (2023.01); A61B 1/00 (2006.01);
U.S. Cl.
CPC ...
G03B 13/36 (2013.01); H04N 23/67 (2023.01); A61B 1/00009 (2013.01);
Abstract

Provided is an image processing apparatus including a processor. The processor is configured to: reconstruct, by employing an image set acquired by means of an endoscope, three-dimensional information of an imaging subject; estimate, by means of an estimator, imaging-subject distances from the image set by employing a learning parameter; calculate, on the basis of the estimated imaging-subject distances and the imaging-subject distances in the three-dimensional information, a scale coefficient; convert relative dimensions of the three-dimensional information to absolute dimensions by employing the scale coefficient; and output the three-dimensional information containing the absolute dimensions. The learning parameter is determined by learning a plurality of learning images including images of imaging-subject distances outside a measurement range in which imaging-subject distances can be measured on the basis of contrast of the image and a position of an autofocus-lens, as well as imaging-subject distances for each of the learning images.


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