Radiology Report Generation Using Similar-Image Reference Reports
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Solution Overview
Problem
Existing AI-based systems for generating radiology reports suffer from inaccuracies and inconsistencies due to hallucinations, and lack customization to individual user preferences and clinical validity evaluation.
Innovation Solution
A system and method that utilizes an AI analysis model to generate radiology reports by referencing similar medical image-radiology report pairs, incorporating finding labels, and associating non-text analysis results, ensuring reliability and accuracy through user confirmation and catalog management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If AI-based systems generate radiology reports automatically, then productivity is improved, but reliability deteriorates due to hallucinations and inaccuracies
Solution Approach 1:
The system implements feedback by retrieving actual radiology reports from the catalog that correspond to similar images, using these retrieved reports as feedback to guide and constrain the AI model's generation process, thereby reducing hallucinations while maintaining efficient automatic report generation
Solution Approach 2:
The system introduces an intermediary retrieval process that fetches reference reports from the catalog based on image similarity. This intermediary step acts as a mediator between the AI model and final report generation, providing grounded reference information that improves reliability without sacrificing productivity
2Ease of operation
If AI models generate reports without reference, then ease of operation is improved, but manufacturing precision deteriorates due to lack of customization and clinical validity
Solution Approach 1:
The system performs preliminary action by pre-building a catalog of medical images paired with their radiology reports. This pre-prepared reference material enables the retrieval-augmented generation process to operate automatically without manual intervention, maintaining ease of operation while ensuring consistent, high-quality report generation through reference guidance
3Measurement precision
If the system uses a catalog of medical image-report pairs, then measurement precision is improved for report accuracy, but device complexity increases
Solution Approach 1:
The system uses copying by retrieving existing radiology reports from the catalog that are paired with similar medical images. Instead of generating reports from scratch, the system copies and adapts proven, accurate reports as references, thereby improving measurement precision while managing device complexity through efficient retrieval operations
Data Source
AI summary
A radiology report generation system is configured to obtain an analysis result for a target medical image using an artificial intelligence analysis model, extract at least one similar image to the target medical image from a catalog set comprising medical image-radiology report pairs; determine at least one radiology report paired with the at least one similar image as a reference image, and generate a radiology report for the target medical image based on the analysis result, using the reference report as a guideline.