MRI Pulse Sequence Configuration Using a Graph Database
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Configuring magnetic resonance imaging systems is complex and requires extensive training, and existing automated protocoling solutions face challenges in achieving robust and standardized workflows.
Innovation Solution
A medical system utilizing a graph database to automatically configure magnetic resonance imaging systems by encoding subject data and pulse sequence configurations, enabling automated protocol generation through a closed control loop.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated protocoling is implemented for MRI examinations, then workload reduction for radiologists is achieved, but system complexity and difficulty of configuration increase
Solution Approach 1:
The patent introduces an intermediary system comprising a graph database and computational system that automatically generates MRI protocols by processing clinical indications and mapping them to appropriate pulse sequences. This intermediary layer handles the complexity of protocol configuration, shielding radiologists from system complexity while delivering automated protocoling benefits and workload reduction.
2Extent of automation
If standardized MRI protocols are implemented across different scanners and vendors, then workflow automation is improved, but adaptability to specific clinical needs decreases
Solution Approach 1:
The system employs dynamic protocol generation where the graph database and computational system automatically adapt MRI protocols based on specific clinical indications, patient data, and scanner capabilities. Rather than using fixed standardized protocols, the system dynamically generates customized protocols that maintain automation benefits while adapting to diverse clinical needs across different scanners and vendors.
3Measurement precision
If comprehensive subject data is collected for automated protocoling, then protocol accuracy is improved, but data processing time and system complexity increase
Solution Approach 1:
The system performs preliminary actions by pre-processing and structuring subject data, clinical indications, and scanner information before automated protocol generation. The graph database is pre-populated with MRI sequence knowledge and relationships, enabling the computational system to quickly retrieve and process relevant information during protocol generation, thereby improving protocol accuracy while minimizing data processing time.
Data Source
AI summary
Disclosed herein is a medical system (100, 300, 500) comprising a memory (116) storing machine executable instructions (120) and a graph database (122). The graph database is configured to output magnetic resonance imaging pulse sequence configuration data (126) in response to receiving subject data. The medical system further comprises a computational system (110). Execution of the machine executable instructions causes the computational system to: receive (200) the subject data; and receive (202) the magnetic resonance imaging pulse sequence configuration data in response to inputting the subject data into the graph database.