Iterative Susceptibility Mapping via Artifact Estimation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current Quantitative Susceptibility Mapping (QSM) techniques face issues with computational streaking artifacts due to the ill-posed nature of the inverse dipole kernel and inaccurate anatomical a priori information, leading to convergence errors and inaccurate susceptibility distribution maps, especially in tissues with strong susceptibility variance.
Innovation Solution
A method involving an iterative process to update error limiting information and susceptibility distribution maps, using preliminary field maps and error limiting information to dynamically adjust a priori information and artifact estimation, ensuring accurate convergence and reduced artifacts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the inverse dipole kernel is used to determine susceptibility distribution map, then the susceptibility mapping can be performed, but computational streaking artifacts appear due to the ill-posed nature and singularity values
Solution Approach 1:
The patent applies preliminary action by performing artifact estimation and removal before final susceptibility map reconstruction. The method estimates streaking artifacts using the inverse dipole kernel and subtracts them from the field map before solving for susceptibility, thereby preventing artifacts from contaminating the final result while maintaining mapping accuracy
Solution Approach 2:
The patent introduces an intermediary artifact estimation map that mediates between the ill-posed inverse problem and the final susceptibility solution. This intermediate representation captures the artifact components separately, allowing them to be removed without affecting the underlying susceptibility information
2Object-affected harmful factors
If truncated k-space QSM method is used to reduce singularity degree, then streaking artifacts are reduced, but susceptibility values become underestimated
Solution Approach 1:
The patent extracts the artifact component from the total field map by estimating it separately using the inverse dipole kernel. By taking out the artifact estimation and removing it before susceptibility reconstruction, the method avoids the need to modify the inverse dipole kernel, thereby preserving susceptibility value accuracy while eliminating artifacts
Solution Approach 2:
The patent converts the harmful streaking artifacts into a beneficial estimation process. By using the inverse dipole kernel to estimate artifacts and then removing them, the method transforms the problematic singularity values into a tool for artifact identification and removal, improving overall solution quality
3Object-affected harmful factors
If a priori information is added to reduce streaking artifacts, then regularization is achieved, but convergence errors occur due to mismatch between a priori information and actual susceptibility distribution
Solution Approach 1:
The patent performs preliminary artifact estimation and removal before applying any regularization based on a priori information. This sequence ensures that the a priori information is applied to an artifact-free field map, preventing convergence errors that would otherwise result from regularizing artifact-contaminated data
Solution Approach 2:
The patent extracts artifacts from the field map before applying a priori information-based regularization. By removing the harmful artifact component first, the subsequent regularization process operates on clean data, ensuring both artifact reduction and convergence accuracy
4Measurement precision
If iterative process is used to update error limiting information and susceptibility distribution, then accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent performs preliminary artifact estimation and removal before initiating the iterative susceptibility reconstruction process. This preliminary step simplifies the subsequent iterative process by removing the dominant artifact component, allowing convergence to be achieved more quickly with fewer iterations
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
The method effectively reduces streaking artifacts and improves the accuracy of susceptibility distribution maps by dynamically updating error limiting information and a priori information, leading to more precise susceptibility mapping.
Implementation Method 1
Magnetic resonance imaging (MRI) uses externally imposed magnetic fields (including a main magnet and a gradient magnet) and radio frequency waves to generate images of an object. The object is magnetized in the externally imposed magnetic fields and generates local magnetic fields.
Implementation Method 2
Almost all material can become magnetized in a magnetic field and then display magnetic effects similar to magnets (e.g. generating a local magnetic field around the material).
Implementation Method 3
Susceptibility property (or referred to as magnetic susceptibility or magnetic susceptibility property) is a measure of the extent of a material becomes magnetized in a magnetic field, or in other words, the intensity of a local magnetic field generated by the material (if magnetized).
Data Source
AI summary
Systems and methods for determining a distribution map of susceptibility property of an object are provided. The method may include one or more of the following operations. A phase diagram corresponding to a magnetic resonance (MR) signal of the object may be obtained. A preliminary field map may be determined based on the phase diagram. Preliminary error limiting information associated with the preliminary field map may be obtained. A preliminary distribution map of susceptibility property of the object may be determined based on the preliminary field map and the preliminary error limiting information. An iteration process including at least one iteration may be performed to determine a target distribution map of susceptibility property of the object.