Medical Image Viewing Protocol Dynamic Highlighting
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Solution Overview
Problem
Current methods for viewing three-dimensional medical imaging data sets are time-consuming and user-dependent, often leading to incomplete inspection of large datasets, and computer-assisted detection (CAD) is not entirely reliable in identifying lesions or pathologies, resulting in missed or incorrectly identified features.
Innovation Solution
A computer-implemented method creates a viewing protocol that dynamically configures image display by identifying sites of interest, using auxiliary information such as CAD data and patient records to adjust rendering parameters and modalities, allowing for enhanced inspection of regions of interest through customized display parameters like magnification, resolution, and interaction options.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual inspection of 3D medical imaging data sets is performed using visualization tools, then the practitioner can inspect the complete data set, but the inspection process is time-consuming and user-dependent
Solution Approach 1:
The viewing protocol dynamically adjusts rendering parameters and automatically navigates through the 3D data set, transforming the static manual inspection process into a dynamic automated workflow that adapts to the data characteristics and highlights regions of interest
Solution Approach 2:
The viewing protocol acts as an intermediary between the raw 3D data and the practitioner, automatically processing and presenting the data in an optimized sequence that reduces the practitioner's workload while maintaining inspection completeness
2Productivity
If CAD is used to identify lesions or pathologies, then the inspection process is automated, but the reliability is reduced due to missed or incorrectly identified features
Solution Approach 1:
The system incorporates feedback mechanisms where CAD results inform the viewing protocol, which then presents targeted views for verification, creating a closed-loop system that improves reliability while maintaining automation benefits
Solution Approach 2:
The viewing protocol applies different display parameters and inspection strategies to different regions of the data set, providing enhanced visualization specifically for areas where CAD has identified potential lesions, thereby improving local inspection quality without compromising overall automation
3Ease of operation
If a simple binary approach is used for CAD results, then the workflow is simple, but important lesions may be missed or incorrectly identified
Solution Approach 1:
The system changes parameters such as rendering resolution, magnification, and display duration for regions of interest, transforming the uniform simple workflow into a multi-parameter workflow that maintains ease of use while improving diagnostic accuracy through enhanced visualization of critical areas
Data Source
AI summary
A method, computer program and device for creating a viewing protocol for medical images is described. At least a first site of interest is identified in a medical imaging data set captured from the patient. Patient record data or computer assisted detection information can be used to identify the site of interest, which may be a potential lesion. A viewing protocol for displaying medical images to a user is planned. The viewing protocol includes a viewing path along which an image of the site of interest will be displayed. The viewing protocol also includes a trigger associated with the site of interest. When the trigger event is encountered the dynamic mode of image display is reconfigured to dynamically highlight the site of interest. The viewing protocol can then be used to control the display of images so as to provide, for example, a virtual endoscope.