MR System Protocol Optimization via Dispersed Data Mining
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Solution Overview
Problem
Purchasers of magnetic resonance systems often lack experience in handling and optimizing these systems, leading to inefficient use of the 3000+ available protocols, resulting in wasted development and validation costs, as well as difficulties in finding the right protocol adjustments, despite customer training and application specialist support.
Innovation Solution
A system and method that evaluates data from geographically dispersed MR system customer sites to identify best-in-class customers' parameters, hardware, and software components, formulating optimized customer-specific protocols by analyzing data using data mining and statistical analysis tools like RapidMiner, and providing customer-specific reports and offers to improve performance and workflows.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If customer training and application specialist support are provided, then customers can access protocols and adjust parameters, but the cost and time required to find optimal settings increases
Solution Approach 1:
The system collects usage data from multiple customer sites, analyzes performance metrics, and provides feedback in the form of optimized protocol recommendations. This closed-loop feedback mechanism enables customers to improve their operational efficiency continuously without requiring extensive training or specialist support at each step.
Solution Approach 2:
The system identifies best-performing protocols from top customers and automatically copies these proven configurations to other customers with similar system characteristics. This eliminates the need for each customer to independently discover optimal settings through trial and error or expert guidance.
2Adaptability or versatility
If 3000+ protocols are made available to customers, then system versatility increases, but development, testing and validation costs increase
Solution Approach 1:
Instead of developing and validating numerous distinct protocols, the system maintains a core set of protocols and optimizes them by changing parameters based on performance data from different customer sites. This parameter-based adaptation approach preserves versatility while significantly reducing development and validation efforts.
Solution Approach 2:
The system creates universal protocol templates that can be automatically adapted to different customer needs through parameter adjustment rather than requiring separate customized protocols for each application. This multi-functional approach allows a single protocol framework to serve multiple purposes across diverse customer sites.
3Adaptability or versatility
If customers customize protocol names and parameters, then customer-specific optimization is achieved, but protocol management complexity increases
Solution Approach 1:
The system extracts the essential optimization logic from complex customer-specific customizations and separates it into reusable pattern templates. This extraction process simplifies protocol management by allowing customers to leverage pre-analyzed optimization patterns rather than managing individual customizations manually.
Data Source
AI summary
A system and method for optimizing customer magnetic resonance systems is provided. An automation system gathers data from a geographically dispersed network of installed magnetic resonance systems, which data is mined and analyzed in order to recognize patterns about the best practices of the installed base. Customer-specific variables for customer magnetic resonance systems are then optimized, based on the recognized patterns. More particularly, customer specific protocols and hardware/software configurations can be calculated and optimized, by making use of data mined from best-in-class customers having similar profiles.