Geometric Coil Compression MR Image Correction
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Solution Overview
Problem
Geometric coil compression in magnetic resonance tomography leads to intensity variations and phase singularities, resulting in cancellation artifacts in reconstructed images, which existing methods have not effectively addressed.
Innovation Solution
The method involves recording a low-resolution prescan MR data record, adjusting it to match the intended higher resolution, generating a compressed prescan data record through geometric coil compression, and using this to correct the compressed scan data record, thereby reducing or eliminating intensity variations and phase singularities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If geometric coil compression is applied to reduce data volume and processing time, then compression rate increases, but intensity variations and phase singularities occur causing cancellation artifacts
Solution Approach 1:
A prescan is performed before the actual scan to capture coil sensitivity information and intensity variation patterns. This preliminary action allows the system to prepare correction factors in advance that will be applied to the compressed scan data, preventing cancellation artifacts while maintaining the benefits of geometric coil compression.
Solution Approach 2:
The system uses the prescan data to generate correction factors that are fed back into the image reconstruction process. These correction factors compensate for intensity variations and phase singularities introduced by geometric coil compression, creating a feedback loop that maintains image quality despite aggressive compression.
2Reliability
If separate reconstruction is performed for each receive coil to maintain image quality, then image quality is preserved, but reconstruction time increases significantly
Solution Approach 1:
The patent combines multiple receive coil data into a reduced set of virtual coils using geometric coil compression. This merging process reduces the number of separate reconstructions needed while maintaining image quality through the application of prescan-based correction factors to the compressed data.
Solution Approach 2:
The system creates virtual coil representations that copy the essential information from multiple physical coils. These virtual coils serve as simplified models that capture the combined signal characteristics, enabling faster reconstruction while preserving the diagnostic information present in the original multi-coil data.
3Measurement precision
If prescan is performed to calibrate and correct the scan data, then image quality and calibration are improved, but additional time and data processing are required
Solution Approach 1:
The prescan uses different acquisition parameters (lower resolution, different sampling density) compared to the actual scan. This parameter change allows faster calibration while capturing sufficient information about coil sensitivities and intensity variations. The corrected scan data then benefits from this efficient prescan calibration.
Data Source
AI summary
Methods are provided for magnetic resonance (MR) image reconstruction. In one exemplary method, a low-resolution prescan MR data record is recorded, the prescan MR data record is adjusted to a provided form of a higher resolution scan MR data record which is likewise to be recorded, a compressed prescan MR data record is generated by geometric coil compression, the scan MR data record is recorded, a compressed scan MR data record is generated by geometric coil compression, and the compressed scan MR data record is then corrected by the compressed prescan MR data record. An MR system includes an MR coil arrangement configured to generate static and high-frequency magnetic fields at the site of an object to be examined and to detect response signals output by the object, and a data processing device configured to process data of the object generated from the response signals, wherein the data processing device is embodied to carry out the method.