MRI Temperature Correction via K-Space Energy Spectrum Analysis
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Solution Overview
Problem
Current magnetic resonance temperature measurement methods are prone to errors due to magnetic field inhomogeneity, leading to incorrect temperature calculations when using theoretical echo times, and existing correction methods are either complex or lack noise robustness.
Innovation Solution
A magnetic resonance temperature correction method based on k-space energy spectrum analysis, where a k-space data matrix is filled with zeros and inverted, allowing for the calculation of actual echo time and temperature variation through pixel intensity variation curves and phase differences, using formulas such as TE_=TE+ΔTE=1BW×Δn and ΔT=Δφα·γ·B0·TE_, to correct for echo time deviations and calculate accurate temperature changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If theoretical echo time TE is used for temperature calculation, then the calculation process is simple, but the temperature measurement accuracy deteriorates due to magnetic field inhomogeneity causing echo time deviation
Solution Approach 1:
The system automatically detects the actual echo time by analyzing the k-space center position and performs self-correction of the temperature calculation, eliminating the need for manual field mapping or complex sequence reprogramming while maintaining high accuracy
Solution Approach 2:
The method changes the parameter used for temperature calculation from the fixed theoretical TE to the dynamically determined actual TE based on k-space analysis, allowing the system to adapt to magnetic field variations without increasing operational complexity
2Measurement precision
If field strength gradient map correction method is used, then temperature measurement accuracy is improved, but the device complexity and operation difficulty increase
Solution Approach 1:
The method extracts only the essential information needed for correction (k-space center position) from the complex field mapping process, discarding unnecessary components while retaining the core correction functionality
Solution Approach 2:
The system uses the existing k-space data structure and Fourier transform processes already present in standard MRI workflows, copying and adapting these existing elements rather than introducing entirely new complex measurement sequences
3Measurement precision
If field strength gradient map correction method is used, then temperature measurement accuracy is improved, but the noise robustness deteriorates
Solution Approach 1:
The method implements feedback by using the detected k-space center position to correct the echo time parameter, which then feeds back into the temperature calculation to compensate for magnetic field variations, creating a self-correcting system that maintains accuracy and robustness
4Measurement precision
If conventional scanning sequence reprogramming is required, then correction accuracy is improved, but the productivity and time efficiency deteriorate
Solution Approach 1:
The correction process is merged with the standard image reconstruction workflow by performing k-space analysis and echo time determination as integral parts of the existing scanning and reconstruction pipeline, eliminating separate correction steps and maintaining high operational efficiency
Data Source
AI summary
Disclosed are a magnetic resonance temperature correction method based on k-space energy spectrum analysis and a system. The method includes: filling a k-space data matrix of magnetic resonance with zeros row by row, and performing an inverse Fourier transform on the k-space data matrix after filling each row of zeros, to obtain a reconstructed image; drawing a pixel intensity variation curve according to a pixel intensity of each pixel in all reconstructed images and a number of rows filled with zeros, and obtaining echo error according to the pixel intensity variation curve, calculation an actual echo time, and calculating a corresponding temperature variation value based on the TE of each pixel.