Endoscope Blur Correction Device Hood Region Segmentation

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Solution Overview

Problem

Conventional blur correction methods in endoscopic examinations can mislead users by moving the region where the hood appears in the image, leading to destabilization of the field of vision and potential misinterpretation of tissue contact during procedures like endoscopic submucosal dissection.

Innovation Solution

A blur correction device and method that differentiate between regions requiring and not requiring blur correction, specifically excluding the hood region from the blur correction process to prevent unnecessary motion and maintain a stable image of the tissue.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Manufacturing precision

If blur correction is applied to the entire image, then image blur is reduced, but the hood region moves causing field of vision destabilization

Engineering Contradiction:

Improveimage blur correctionVSAvoidfield of vision stability

Core Design Contradiction:

Manufacturing precisionVSStability of the object's composition

Solution Approach 1:

The patent divides the image into multiple regions: a first region containing the hood where blur correction is not applied, and a second region excluding the hood where blur correction is applied. This segmentation allows different processing treatments for different regions, preventing hood movement while correcting tissue blur.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent applies local quality by making the blur correction processing section output different results for different regions. The first region (hood area) maintains its original appearance without correction, while the second region (tissue area) receives blur correction, creating locally optimized image quality.

Inventive Principle:

Principle #3Local quality

2Manufacturing precision

If blur correction is applied to the hood region, then image blur is reduced, but tissue contact detection accuracy decreases

Engineering Contradiction:

Improveimage blur correctionVSAvoidtissue contact detection accuracy

Core Design Contradiction:

Manufacturing precisionVSMeasurement precision

Solution Approach 1:

The patent extracts the hood region from the blur correction process by defining a first region that excludes the hood from the second region where blur correction is applied. This extraction ensures that the hood remains stationary in the image while only the tissue regions benefit from blur correction, maintaining detection accuracy.

Inventive Principle:

Principle #2Taking out (Extraction)

3Productivity

If conventional blur correction is used, then examination efficiency improves, but user confusion increases due to hood movement

Engineering Contradiction:

Improveexamination efficiencyVSAvoiduser confusion

Core Design Contradiction:

ProductivityVSObject-generated harmful factors

Solution Approach 1:

By segmenting the image into hood region and tissue region with different processing treatments, the patent maintains examination efficiency through blur correction while preventing the harmful effect of hood movement that causes user confusion.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent converts the potential harm of hood movement (which causes confusion) into a benefit by deliberately excluding the hood from blur correction processing. This ensures the hood remains a stable visual reference while still providing blur correction benefits to the tissue regions.

Inventive Principle:

Principle #22Blessing in disguise (Convert harm into benefit)

Data Source

PatentUS11196926B2Blur correction device, endoscope apparatus, and blur correction method

Publication Date: 2021.12.07 OLYMPUS CORPORATION(JP)

AI summary

A blur correction device includes a processor including hardware, and the processor obtains an object image from an imaging section, sets any one of a first region where a blur correction is not applied and a second region where the blur correction is applied, based on the object image, finds a third region representing a result of the blur correction applied to the second region, and combines the third region and the first region.