Magnetic Particle Imaging Reconstruction via Non-Ideal FFP Signal Transformation
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Solution Overview
Problem
Existing Magnetic Particle Imaging (MPI) methods fail to accurately reconstruct images due to non-ideal Field Free Point (FFP) conditions in actual devices, leading to errors and artifacts, as they assume an ideal FFP where all positions are field-free, which is not feasible in practice.
Innovation Solution
A magnetic particle imaging method is developed that constructs a magnetic field response model for non-ideal FFPs, analyzing the difference in voltage signals between ideal and non-ideal FFPs to provide an image reconstruction algorithm, which involves setting external magnetic field conditions, obtaining magnetization vectors and Point Spread Functions, performing integral transformations, and averaging moving speeds to achieve equivalent ideal FFP signals for high-quality image reconstruction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If ideal FFP conditions are assumed for image reconstruction, then the reconstruction algorithm is simple, but image quality deteriorates due to artifacts and phase errors caused by non-ideal FFP conditions
Solution Approach 1:
The patent transforms the reconstruction problem by changing parameters: instead of reconstructing directly from non-ideal FFP signals, it converts them to equivalent ideal FFP signals through integral transformation and moving speed averaging, then applies standard reconstruction algorithms. This parameter transformation resolves the contradiction by maintaining algorithm simplicity while achieving accurate reconstruction under non-ideal conditions.
2Measurement precision
If non-ideal FFP conditions are addressed through complex signal processing, then image reconstruction quality improves, but the processing complexity increases
Solution Approach 1:
The patent introduces an intermediary transformation process: it uses integral transformation to convert non-ideal FFP voltage signals into equivalent ideal FFP signals, and employs moving speed averaging as an intermediary step to normalize the signals. These intermediary processes bridge the gap between non-ideal measurements and ideal reconstruction requirements, improving quality without requiring overly complex processing.
3Area of stationary object
If SPIOs are subjected to DC magnetic field in non-ideal FFP, then spatial coding is affected, but this condition is inevitable in actual MPI devices with large view field
Solution Approach 1:
The patent converts the harmful effect of DC magnetic field-induced asymmetric excitation into a beneficial solution: it derives the relationship between non-ideal FFP signals and ideal FFP signals, showing that through integral transformation and moving speed averaging, the asymmetric excitation effects can be compensated. This transforms the inevitable non-ideal condition into a manageable parameter that can be corrected through signal 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 method reduces artifacts and phase errors, improves image reconstruction quality and resolution, and is applicable to various FFP-MPI devices and tracers, enabling high-precision imaging even with non-ideal FFP conditions, and supports large view-field MPI.
Implementation Method 1
the SPIOs in other areas are in a magnetic saturation state under a combined action of the selection field and the focusing field and do not have a response to the excitation magnetic field
Implementation Method 2
Superparameteric Iron Oxide Nanoparticles (SPIOs) in the FFP area generate a response to an excitation magnetic field
Implementation Method 3
a voltage signal collected by a detection coil only includes a magnetic particle response in the FFP area
Data Source
AI summary
A magnetic particle imaging method based on a non-ideal Field Free Point (FFP), including the following steps: setting external magnetic field conditions of a non-ideal FFP and an ideal FFP, and obtaining a magnetization vector M of Superparamagnetic Iron Oxide Nanoparticles (SPIOs) and a Point Spread Function (PSF) in combination with a Langevin function; obtaining a signal feature on basis of a voltage signal of a detection coil of a Magnetic Particle Imaging (MPI) instrument; performing integral transformation on the voltage signal collected by the detection coil of the MPI instrument to obtain a voltage signal of an equivalent ideal FFP; averaging the moving speed of an FFP of the MPI instrument to obtain a moving speed of the equivalent ideal FFP; obtaining an equivalent Three-Dimensional concentration reconstruction image on basis of the voltage signal of the equivalent ideal FFP and a moving speed of the equivalent ideal FFP.