Multi-Parameter Image Sampling for Faster Medical Review
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Solution Overview
Problem
Conventional medical imaging review processes are time-consuming and prone to human error due to manual adjustment of multiple parameters, increasing operational costs and decreasing the quality of service.
Innovation Solution
A multi-parameter sampling tool integrated with an image review application that automatically configures workflow tool parameters based on pixel data from a selected region of interest, reducing the need for manual adjustments and optimizing image display.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual adjustment of multiple parameters is performed for each workflow tool, then accurate assessment can be made, but review time increases and operational costs increase
Solution Approach 1:
The system performs self-service by automatically determining optimal parameter settings for workflow tools based on pixel data from the image itself. The sampling tool analyzes the image content and autonomously configures parameters such as window width, window level, and contrast settings without requiring manual adjustment by the user, thereby reducing review time while maintaining assessment accuracy.
Solution Approach 2:
The system dynamically changes parameters based on the analyzed pixel data from the region of interest. By extracting statistical information from the image pixels and automatically adjusting workflow tool parameters accordingly, the system adapts the imaging parameters to the specific characteristics of the medical image being reviewed, eliminating the need for time-consuming manual parameter tuning.
2Measurement precision
If manual adjustment of multiple parameters is performed for each workflow tool, then accurate assessment can be made, but likelihood of human error increases
Solution Approach 1:
The system eliminates human error by performing self-service parameter configuration. The automated sampling tool objectively analyzes pixel data and determines optimal parameters without human intervention, removing the possibility of subjective errors, fatigue-related mistakes, or inconsistent parameter selection that occur with manual adjustment.
Solution Approach 2:
The system implements feedback by continuously analyzing the pixel data from the image and using this information to automatically adjust and optimize workflow tool parameters. This closed-loop approach ensures that parameters are consistently set based on objective image characteristics rather than subjective human judgment, improving reliability.
3Adaptability or versatility
If multiple workflow tools are used for image review tasks, then comprehensive analysis can be performed, but device complexity increases
Solution Approach 1:
The sampling tool is designed as a universal multi-functional instrument that can determine parameters for multiple different workflow tools (windowing, contrast adjustment, edge enhancement, etc.) through a single automated process. This single tool performs the function of what would otherwise require multiple separate manual configuration processes, reducing system complexity while maintaining comprehensive analysis capabilities.
4Ease of operation
If manual parameter settings are adjusted for each tool, then precise control can be achieved, but operational costs increase
Solution Approach 1:
The system achieves precise parameter control through self-service automation. The sampling tool independently analyzes the image and determines the optimal parameters without requiring operator time and expertise for manual adjustment. This automation reduces operational costs associated with radiologist time while maintaining precise control over imaging parameters through objective algorithmic determination.
Data Source
AI summary
A system may include a processor-based device storing or accessing an image review application, which when executed by the processor-based device, causes acts to be performed such as retrieving image data for populating a graphical user interface displayed on the processor-based device and receiving a user input selecting a workflow tool and a sampling tool. The sampling tool, when executed by the processor-based device, may also receiving an additional user input of a region of interest within the image data, determining values for a parameter of interest based on the pixels within the region of interest, automatically configuring the workflow tool based on the determined values for the parameter of interest, and generating preset parameters of the workflow tool. The image review application may also adjust the display of the image data on the GUI using the configured workflow tool.