MRI Calibration via Subject-Specific Image Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current MRI systems face challenges in accurately and efficiently calibrating system parameters, such as the radiofrequency and magnetic fields, due to complex manual operations, which can decrease the quality and accuracy of image data.
Innovation Solution
A system and method that utilize a processor to analyze image data from a subject, determine characteristics like position and water content, and adjust individualized parameters for the imaging device, including calibration parameters for the magnetic and radiofrequency fields, using a trained machine learning model to improve calibration accuracy and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual calibration operations are performed for MRI system parameters, then the operator can adjust settings, but the accuracy and efficiency of calibration decrease due to complexity
Solution Approach 1:
The system automatically determines individualized parameters and calibration settings without requiring manual operator intervention. The processor analyzes image data and autonomously adjusts MRI system parameters, allowing the system to calibrate itself based on detected subject characteristics.
Solution Approach 2:
The patent replaces manual mechanical calibration operations with an automated computational system. Instead of operators physically adjusting controls, a processor analyzes image data and automatically determines calibration parameters, substituting human mechanical operations with electronic computation and automated control.
2Measurement precision
If manual calibration operations are performed for MRI system parameters, then the operator can adjust settings, but the time required for calibration increases
Solution Approach 1:
The system performs preliminary analysis of subject characteristics from image data before the actual MRI scanning begins. By determining individualized parameters in advance based on scout images or preliminary scans, the system prepares calibration settings beforehand, eliminating the need for time-consuming manual calibration during the imaging process.
Solution Approach 2:
The automated system independently performs calibration without requiring operator time and effort. The processor continuously monitors and adjusts parameters based on real-time image data, allowing the system to self-calibrate while scanning, thereby eliminating dedicated calibration time.
3Manufacturing precision
If individualized parameters are determined based on subject characteristics, then image quality improves, but the processing complexity increases
Solution Approach 1:
The patent replaces complex manual analysis and parameter determination with automated image processing algorithms. The processor automatically extracts subject characteristics from image data and computes individualized parameters, substituting human expert analysis with computational algorithms that handle the complexity internally.
Solution Approach 2:
The system introduces an intermediary processing layer between image acquisition and MRI parameter setting. This intermediary component analyzes image data to extract subject characteristics and translates them into appropriate calibration parameters, mediating between raw data and final settings while managing the complexity of the transformation process.
4Productivity
If automated parameter determination is implemented, then calibration efficiency improves, but the system complexity increases
Solution Approach 1:
The processor is designed to perform multiple functions: acquiring image data, analyzing subject characteristics, determining individualized parameters, and controlling MRI system settings. By consolidating these diverse functions into a single multi-functional processing system, the patent achieves automated calibration efficiency while managing overall system complexity through functional integration.
Solution Approach 2:
The system merges image processing, characteristic analysis, parameter determination, and calibration control into an integrated automated workflow. By combining these previously separate operations into a unified system that processes data continuously, the patent achieves efficient automated calibration without requiring multiple independent complex subsystems.
Data Source
AI summary
A method may include obtaining image data of a subject acquired by an imaging device. The method may also include determining one or more characteristics associated with a body part of the subject from the image data. The one or more characteristics of the body part of the subject may include at least one of position information of the body part in the subject, geometric morphology information of the body part, water content information, or fat content information. The method may also include determining, based on one or more characteristics associated with the body part, values of one or more individualized parameters corresponding to the subject. The method may further include causing the imaging device to perform an imaging scan on the subject according to the values of the one or more individualized parameters.