Urinary Sediment All-Component Image Generation via Flow Cell Imaging

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Solution Overview

Problem

Existing urinary sediment examination methods, particularly those using a flow method, fail to provide an image that includes multiple material components, limiting the ability to observe their distribution and states at a glance.

Innovation Solution

A measurement system and information processing device that captures images of a urine sample using a flow cell, categorizes and counts material components, and generates an all-component image resembling microscopic observation by arranging non-overlapping, focused images based on calibration curves and correction coefficients, allowing for a comprehensive view of multiple components.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If image capture is performed using a flow method, then automation and efficiency are improved, but the ability to observe distribution and states of multiple material components at a glance deteriorates

Engineering Contradiction:
Improveautomation efficiencyVSAvoiddistribution and state information of material components
Core Design Contradiction:
ProductivityVSLoss of information

Solution Approach 1:

The invention creates a synthetic composite image that copies the visual appearance of a microscopic whole visual field examination. This composite image is generated by extracting material component images from flow method captured images, categorizing them by type, and arranging them in a synthetic visual field that mimics the appearance of observing all components simultaneously, thus recovering the distribution and state information that would otherwise be lost

Inventive Principle:
Principle #26Copying

Solution Approach 2:

The invention transitions from capturing images in the temporal dimension (sequential frames of flowing sample) to presenting information in a spatial dimension (synthetic composite image showing all components arranged in a visual field). This dimensional transformation allows the system to maintain automation while providing a comprehensive overview similar to microscopic examination

Inventive Principle:
Principle #17Another dimension (Dimensionality change)

2Measurement precision

If material component images are extracted and categorized for analysis, then measurement precision is improved, but the retention of captured images for comprehensive observation deteriorates

Engineering Contradiction:
Improvematerial component categorization accuracyVSAvoidnumber of retained captured images
Core Design Contradiction:
Measurement precisionVSQuantity of substance

Solution Approach 1:

The invention extracts only the essential material component images from the captured sequence, separating them from the continuous flow of captured images. By extracting and categorizing only the relevant component images needed for analysis and composite image generation, the system achieves precise measurement while avoiding the need to retain all captured images, thus reducing data storage requirements

Inventive Principle:
Principle #2Taking out (Extraction)

Data Source

PatentEP3647998B1Information processing device, information processing method, measurement system and non-transitory storage medium
Publication Date: 2025.08.20 ARKRAY INC
  • EP3647998B1 patent drawingFigure 1
  • EP3647998B1 patent drawingFigure 2
  • EP3647998B1 patent drawingFigure 3

AI summary

An information processing device includes a categorizing section configured to extract a material component image identified as a material component from plural images obtained by imaging a sample fluid containing a plurality of types of material components and flowing through a flow cell, and to categorize the extracted material component image by predetermined category, a count derivation section configured to derive a count of the material component per standard visual field, or derive a count per unit liquid volume of the material component contained in the sample fluid, for each of the categories based on the number of material component images categorized by the categorizing section, and a generation section configured to generate an all-component image in which the material component images are arranged according to the counts that have been derived by the count derivation section for each of the categories.