Automated Finding Matching in Medical Imaging Studies
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Radiologists face a time-consuming and monotonous task when comparing follow-up imaging studies to identify and annotate changes in treated lesions or intervention results, as they need to visually match hundreds of images between prior and current studies, often missing findings or requiring extensive scanning.
Innovation Solution
A system that detects the observer's focus of attention on anatomical images, maps this attention to the image geometry, and compares it with previous studies to visually display matching or missing findings, reducing the need for extensive scrolling and annotation by automatically identifying corresponding images and providing graphical feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If radiologists manually scroll through and visually compare hundreds of images between prior and current studies, then they can identify changes in lesions, but the process becomes time-consuming and monotonous
Solution Approach 1:
The patent replaces the manual mechanical process of scrolling and visual comparison with an automated computer-based system that uses image processing algorithms to automatically compare findings between prior and current studies, significantly reducing time while maintaining accuracy
Solution Approach 2:
The system creates and compares digital representations of anatomical findings across multiple time points, using stored image data and automated analysis to identify changes without requiring manual review of each image sequence
2Reliability
If radiologists manually locate and compare each finding between studies, then they can annotate changes, but the task becomes monotonous and error-prone
Solution Approach 1:
The system performs self-service by automatically identifying, comparing, and highlighting changes between studies without requiring manual intervention, thereby improving reliability while simplifying the radiologist's role to verification and final annotation
Solution Approach 2:
The system provides automated feedback by highlighting detected changes and presenting them to the radiologist for verification, creating a feedback loop that improves both reliability and operational ease by reducing manual search and comparison tasks
3Reliability
If radiologists review all image slices to ensure complete coverage, then they can avoid missing findings, but the scan extent and radiation dose increase
Solution Approach 1:
The system performs preliminary automated analysis of image data to identify potential findings and changes before final review, allowing radiologists to focus only on relevant areas and reduce the extent of scanning required in follow-up studies
Solution Approach 2:
The system changes the approach from comprehensive manual review of all slices to targeted automated analysis with adjusted scanning parameters, maintaining detection completeness while reducing radiation exposure through optimized scan extents
Data Source
AI summary
A method includes detecting a focus of attention of an observer of an anatomical image of a set of images, determining a location of the anatomical image includes tissue with a finding of interest based on the detected focus of attention, identifying an anatomical image, from an earlier acquired imaging data set, with a same portion of tissue as the displayed image, visually displaying graphical indicia, concurrently with the displayed image, that identifies the earlier acquired image.