Cell Image And Count Analysis for Accessible Disease Differentiation

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Solution Overview

Problem

Conventional disease differentiation methods require complex test steps and skilled examiners, making them cumbersome and limiting their accessibility.

Innovation Solution

A disease differentiation support method using a computer algorithm that generates differentiation support information based on first parameters obtained from analyzing cell images and second parameters related to cell counts, utilizing a combination of deep learning algorithms and machine learning algorithms to simplify the process.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If conventional test methods are used for disease differentiation, then measurement precision can be maintained, but device complexity and difficulty of operation increase significantly

Engineering Contradiction:

Improvedisease differentiation accuracyVSAvoidtest procedure complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent replaces manual mechanical examination processes with automated image analysis systems. The system captures images of cells in blood smears and uses automated algorithms to analyze cell morphology, replacing the need for skilled examiners to manually examine and differentiate disease states, thereby maintaining precision while reducing operational complexity

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent introduces an intermediary image analysis system that acts as a bridge between the sample and the diagnosis. The system processes images through multiple analysis stages (first parameter extraction, second parameter extraction, and integrated analysis) to generate differentiation support information, simplifying the overall diagnostic process while maintaining accuracy

Inventive Principle:

Principle #24Intermediary (Mediator)

2Measurement precision

If conventional test methods are used for disease differentiation, then measurement precision can be maintained, but ease of operation deteriorates due to requirement for skilled personnel

Engineering Contradiction:

Improvedisease differentiation accuracyVSAvoidoperational accessibility

Core Design Contradiction:

Measurement precisionVSEase of operation

Solution Approach 1:

The system performs self-service by automatically analyzing cell images and generating differentiation support information without requiring skilled examiners. The automated analysis includes extracting first parameters (cell morphology features), second parameters (cell count and distribution), and integrating them to produce diagnostic support, enabling any operator to perform accurate disease differentiation

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces the mechanical skill-based examination process with an automated digital system that captures and analyzes cell images, substituting human expertise with algorithmic processing to improve ease of operation while maintaining diagnostic precision

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Productivity

If automated image analysis is implemented, then ease of operation and productivity improve, but measurement precision may deteriorate without skilled examiner judgment

Engineering Contradiction:

Improvetest processing efficiencyVSAvoiddisease differentiation accuracy

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The patent segments the analysis process into distinct stages: first parameter extraction (cell morphology), second parameter extraction (cell count and distribution), and integrated analysis. This segmentation allows each stage to be optimized independently while maintaining overall precision, with the computer algorithm synthesizing results from multiple analysis dimensions to achieve accurate differentiation

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent adds another dimension to the analysis by integrating both first parameters (morphological features) and second parameters (quantitative cell data) in a multi-dimensional analysis space. This dimensional expansion enables the system to capture complex disease patterns that would be difficult to detect through single-parameter analysis, maintaining precision while enabling automation

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

Data Source

PatentUS20260016392A1Disease differentiation support method, disease differentiation support apparatus, and disease differentiation support computer program

Publication Date: 2026.01.15 SYSMEX CORP

AI summary

Disclosed is a disease differentiation support method for supporting disease differentiation, the disease differentiation support method including: obtaining a first parameter obtained by analyzing an image including a cell contained in a sample collected from a subject; obtaining a second parameter regarding a number of cells contained in the sample; and generating, by using a computer algorithm, differentiation support information for supporting disease differentiation, on the basis of the first parameter and the second parameter.