B0 Field Drift Correction in MR Temperature Mapping
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Solution Overview
Problem
The precision of temperature maps generated by magnetic resonance tomography is impaired by B0 field drift, leading to errors in temperature difference determination due to inability to differentiate temperature changes from B0 field-dependent phase changes, and existing correction methods are error-prone and require manual selection of correction regions.
Innovation Solution
A method that calculates fluctuation measurements per pixel from phase images or temperature maps, identifying pixels with low fluctuation for automated selection of correction regions, calibrating these pixels to corresponding pixels in a reference image or map to correct B0 field drift, and continuously adapting the correction mask to account for subject movements and temperature changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual selection of correction regions is used to correct B0 field drift, then correction can be applied, but the process becomes complex and error-prone requiring expertise in temperature-stable regions
Solution Approach 1:
The system automatically identifies correction regions by analyzing temperature stability characteristics of different body regions, eliminating the need for manual expert selection. The correction mask is generated autonomously based on fluctuation measurements, making the process self-service and reducing operational complexity
Solution Approach 2:
A correction mask is introduced as an intermediary element that selectively weights pixels based on their temperature stability. This mask acts as a mediator between the raw temperature data and the final corrected temperature difference, automatically identifying reliable correction regions without manual intervention
2Reliability
If correction regions are manually selected, then B0 field drift correction can be performed, but operator expertise in identifying temperature-stable regions is required
Solution Approach 1:
The system performs self-service by automatically analyzing temperature fluctuations across different body regions and autonomously generating the correction mask. This eliminates the need for operators to manually identify temperature-stable regions, making the process accessible without specialized expertise while maintaining high reliability
Solution Approach 2:
The system uses feedback from temperature fluctuation measurements to automatically adjust and optimize the correction mask. By continuously monitoring which regions exhibit temperature stability, the system self-corrects and refines its selection of correction regions, ensuring reliability without manual intervention
3Ease of operation
If B0 field drift is not corrected, then the process remains simple, but temperature map precision deteriorates due to inability to differentiate temperature changes from B0 field-dependent phase changes
Solution Approach 1:
The correction mask serves as an intermediary that selectively applies corrections only to regions with stable temperature characteristics. This intermediary approach maintains process simplicity by automating the correction application while significantly improving temperature difference precision through intelligent region selection
Solution Approach 2:
The correction is applied locally to specific regions identified as temperature-stable, rather than uniformly across the entire image. This local quality approach ensures that corrections are applied only where reliable, maintaining precision while keeping the overall process simple through automated region-specific processing
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach simplifies and automates B0 field drift correction, reducing errors by distinguishing between temperature changes and B0 field-induced changes, and ensures foolproof operation without requiring expertise in temperature-stable regions, enhancing the accuracy and reliability of temperature map generation.
Implementation Method 1
The nuclear magnetic resonance frequency of hydrogen atoms (protons) in a water molecule (and thus in particular in the water molecules of the patient's body) exhibit a characteristic temperature dependency.
Implementation Method 2
The B0 field drift is a slow variation of the basic magnetic field (B0 field) of the MR scanner that is used to generate the temperature map.
Data Source
AI summary
In a method and device for correction of a B0 field drift in a temperature map acquisition by magnetic resonance tomography, a fluctuation measurement is calculated per pixel from a number of magnetic resonance tomography phase images of an examination subject or from temperature maps derived therefrom. Using this fluctuation measurement, pixels of the phase images or temperature maps with low fluctuation are determined, and corresponding pixels of a phase image to be corrected or of a temperature map to be corrected are selected using the pixels determined as having low fluctuation. The phase image to be corrected or the temperature map to be corrected is adjusted to a reference phase image or a reference temperature map such that the selected pixels of the phase image to be corrected or of the temperature map to be corrected are calibrated to corresponding pixels of the reference phase image or of the reference temperature map.