Medical Image Analysis Validation Interface

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Solution Overview

Problem

Existing medical image processing systems lack the capability to obtain active and explicit approval from doctors for analysis results, relying solely on manual validation which can be inefficient and prone to errors.

Innovation Solution

A medical image processing apparatus that includes a display unit to show medical images and analysis results, along with input receiving and storage units, allowing doctors to actively and explicitly approve or correct analysis results through a user-friendly interface.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If manual validation of medical image analysis results is used, then doctors can review and approve results, but the process becomes time-consuming and inefficient

Engineering Contradiction:
Improvevalidation accuracyVSAvoidvalidation time
Core Design Contradiction:
ReliabilityVSLoss of time

Solution Approach 1:

The system performs preliminary analysis of medical images using AI algorithms before presenting results to doctors. The analysis results are prepared and displayed in advance, allowing doctors to review pre-processed information rather than performing manual analysis from scratch, thus reducing validation time while maintaining reliability

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

The system implements a feedback mechanism where doctors can provide corrections or approvals of AI analysis results. This feedback is used to improve future analysis accuracy and to track validation patterns, enabling the system to learn from doctor decisions and reduce unnecessary manual review time for high-confidence results

Inventive Principle:
Principle #23Feedback

2Reliability

If explicit approval mechanisms are implemented, then diagnostic reliability improves, but the operational complexity increases

Engineering Contradiction:
Improvediagnostic reliabilityVSAvoidsystem complexity
Core Design Contradiction:
ReliabilityVSDevice complexity

Solution Approach 1:

The approval process is segmented into discrete, manageable steps: image display, analysis result presentation, individual result approval/correction, and final confirmation. Each step is independently controllable and can be completed separately, reducing the perceived complexity while ensuring comprehensive validation

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The system acts as an intermediary between AI analysis and final diagnosis, providing a structured interface that mediates the approval process. The interface presents analysis results in a standardized format and captures doctor decisions systematically, simplifying the interaction while maintaining diagnostic reliability

Inventive Principle:
Principle #24Intermediary (Mediator)

Data Source

PatentEP3649917B1Medical image processing device, endoscope device, diagnostic support device, medical service support device, and report generation support device
Publication Date: 2025.05.28 FUJIFILM CORP
  • EP3649917B1 patent drawingFigure 1~2
  • EP3649917B1 patent drawingFigure 3~4
  • EP3649917B1 patent drawingFigure 5~6

AI summary

Provided are a medical image processing apparatus, an endoscope apparatus, a diagnostic support apparatus, a medical service support apparatus, and a report creation support apparatus that can obtain an active and explicit approval for an analysis result of a medical image from a doctor. A medical image processing apparatus 10 includes a medical image acquisition unit 11 that acquires a medical image 50 including a subject image, a medical image analysis result acquisition unit 12 that acquires an analysis result obtained by analyzing the medical image 50, a display unit 13 that displays at least one medical image 50 and at least information on presence or absence of a lesion or a type of a lesion in the analysis result acquired by the medical image analysis result acquisition unit 12, and an input receiving unit 14 that receives an input regarding whether or not the information on presence or absence of a lesion or a type of a lesion included in the analysis result is correct.