High-robustness fast imaging method and device combining k space and image space reconstruction

Abstract

The invention discloses a high-robustness fast imaging method and device combining k space and image space reconstruction, and belongs to the field of magnetic resonance imaging. The method is used for reconstructing a variable acceleration undersampling image frame formed by a measured object in magnetic resonance parameter measurement, and comprises the following steps of: firstly, reconstructing an undersampling image frame with a lower acceleration factor and an automatic calibration signal by using a k-space automatic calibration method, and then exporting an automatically optimized sensitivity graph and a correction factor graph from the undersampling image frame; in this way, under-sampled image frames with other higher acceleration factors can be reconstructed. According to the method, the traditional sensitivity graph can be combined with the sensitivity graph obtained by decomposing the subspace model to realize automatic optimization, so that high-robustness accurate reconstruction from height undersampling data is realized, and the speed is four times or more than four times that of a common method. The method serves as a self-calibration reconstruction method, does not need a full sampling frame, and is particularly suitable for accelerating three-dimensional multi-frame magnetic resonance imaging.

Description

technical field [0001] The invention belongs to the field of magnetic resonance imaging, and can realize highly robust and fast imaging for magnetic resonance parameter measurement requiring multiple frames of image data. Background technique [0002] Magnetic resonance imaging (MRI) can be used to measure various physiological parameters and has been shown to quantitatively assess various pathological information, such as longitudinal relaxation time (T 1 ), the transverse relaxation time (T 2 ), apparent diffusion coefficient (ADC), amide proton transfer (APT), etc. Quantitative measurement of physiological parameters requires the acquisition of multiple data sets with modulation of pulse train parameters such as echo time (TE), flip angle (FA), inversion time (TI), or saturation frequency. The signal evolution in the multipart dataset is then fitted according to a parametric model to achieve pixel-by-pixel parameter estimation. MRI parameter measurement scan time is lo...

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Problems solved by technology

[0006] The purpose of the present invention is to solve the problems of long scanning time of multi-frame imaging technology, inaccurate coil sensitivity map of existing acceleration technology, etc., and provide a highly robust fast imaging method combined with k-space and image space reconstruction (English name is joint K-space and Image-space Parallel Imaging with high Robustness (hereinafter referred to as the RobustKIPI method) and device, which can automatically optimize the sensitivity map and accurately reconstruct images from highly undersampled data

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