Method and system for reconstructing incoherent motion magnetic resonance imaging parameters in voxels

Abstract

The invention discloses a method and system for reconstructing incoherent motion magnetic resonance imaging parameters in voxels. The method comprises the following steps: setting a parameter D, a parameter f, a parameter D * and a parameter S (0) in a geometric figure generated in a simulation area, and judging whether the total area of all geometric figures covers the simulation area or not; ifso, generating a D parameter graph, an f parameter graph, a D * parameter graph and an S (0) parameter graph; generating a magnetic resonance diffusion weighted image corresponding to each b value, and training the neural network model to obtain a trained neural network model; and performing Fourier transform and normalization processing on the k-space data, and inputting the normalized magnetic resonance diffusion weighted image into the trained neural network model to obtain a reconstructed IVIM parameter image. By adopting the method and the system provided by the invention, the problem that the reconstruction result presents granular sensation due to point-by-point fitting is solved, the image is smoother, the influence of the small b value on the IVIM double-exponential model is considered, and the reconstruction effect is improved.

Description

technical field [0001] The invention relates to the technical field of magnetic resonance imaging, in particular to a method and system for reconstructing magnetic resonance imaging parameters of incoherent motion within a voxel. Background technique [0002] Magnetic Resonance Imaging (MRI) is widely used in clinical diagnosis due to its advantages of high soft tissue resolution, no ionizing radiation, and multi-directional and multi-parameter imaging. Magnetic resonance diffusion weighted imaging (DWI) mainly depends on the movement of water molecules rather than the spin proton density of tissue, T 1 value or T 2 Therefore, it is possible to detect the diffusion movement of water molecules in living tissue. The commonly used diffusion-weighted imaging sequence is the EPI-DWI sequence, which mainly adds a diffusion gradient on the basis of the echo planar imaging (EPI) sequence. Areas of weaker intensity show hyperintensity and areas of intense diffusion appear as hypoi...

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Problems solved by technology

[0004] Although the IVIM model has successfully solved the limitations of the traditional single-exponential model, the model has a high degree of freedom and requires point-by-point nonlinear fitting for each pixel of the entire set of images, which makes the reconstruction of the D and f parameter maps It takes a lot of time, and the reconstructed parameter map will show obvious graininess, which will affect clinical diagnosis

At the same time, in the traditional point-by-point nonlinear fitting method, in order to alleviate the problem of high degrees of freedom in the double-exponential model of incoherent motion within the voxel, only large b values ​​(b≥200) are used for fitting the D and f parameter maps The original data (b represents the gradient factor), ignoring the impact of the small b value (b<200) data, resulting in the result cannot fully match the double exponential model, which may affect the diagnosis result

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