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Quantitative imaging method and device of magnetic resonance

An imaging method and magnetic resonance image technology, applied in the field of medical imaging, can solve the problems of low accuracy of quantitative values, long scanning time, long calculation time, etc., to reduce calculation time, fast image reconstruction rate, and improve quantitative magnetic resonance imaging. effect of speed

Active Publication Date: 2018-11-27
SHANGHAI NEUSOFT MEDICAL TECH LTD
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  • Abstract
  • Description
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  • Application Information

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Problems solved by technology

However, the existing magnetic resonance imaging has the defect of long scanning time, and the imaging mathematical model used to calculate the quantitative magnetic resonance is often a simplified description of the real world, ignoring the influence of many factors. In this way, the quantitative calculation based on the mathematical model The accuracy of the value is low. In addition, the process of fitting calculation is often non-linear, resulting in long calculation time

Method used

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  • Quantitative imaging method and device of magnetic resonance

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Embodiment 1

[0092] It should be noted that in the embodiment of the present application, the reconstruction of each echo magnetic resonance image is jointly completed by using the parallel imaging method and the sequential combination of Model1. Moreover, in order to take advantage of the parallel imaging method and the image reconstruction by DNN, the parallel imaging method can complete a part of the image reconstruction process, and the DNN image reconstruction method can complete the remaining part of the image reconstruction process.

[0093] See image 3 , the magnetic resonance quantitative imaging method provided in the embodiment of the present application includes the following steps:

[0094] S301: Collect partial k-space data of multiple echoes according to a down-sampling manner to obtain k-space collected data of multiple echoes.

[0095] In this embodiment, in order to realize quantitative magnetic resonance imaging, k-space data corresponding to multiple echoes need to be...

Embodiment 2

[0116] It should be noted that Embodiment 2 has many similarities with Embodiment 1. For the sake of brevity, only the differences are improved here. For similarities, please refer to the corresponding description of Embodiment 1.

[0117] See Figure 4 , is a flowchart of the magnetic resonance quantitative imaging method provided in Embodiment 2 of the present application. Such as Figure 4 As shown, the magnetic resonance quantitative imaging method includes:

[0118] S401: Acquire partial k-space data of multiple echoes according to a down-sampling manner, and obtain k-space acquisition data of multiple echoes.

[0119] S402: Using a parallel imaging method to partially reconstruct the k-space acquisition data of each echo to obtain a first image of each echo.

[0120] S403: According to the first image of each echo and the first deep neural network model, perform complete reconstruction through the first deep neural network model to obtain a second image of each echo, ...

Embodiment 3

[0128] It should be noted that the third embodiment has many similarities with the second embodiment. For the sake of brevity, only the differences are improved here. For the similarities, please refer to the corresponding description of the second embodiment.

[0129] See Figure 5 , is a flow chart of the magnetic resonance quantitative imaging method provided in Embodiment 3 of the present application. Such as Figure 5 As shown, the magnetic resonance quantitative imaging method includes:

[0130]S501: Acquire partial k-space data of multiple echoes according to a down-sampling manner, and obtain k-space acquisition data of multiple echoes.

[0131] S502: Using a parallel imaging method to partially reconstruct the k-space acquisition data of each echo to obtain a first image of each echo.

[0132] S503: According to the first image of each echo and the first deep neural network model, perform complete reconstruction through the first deep neural network model to obtain...

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Abstract

The invention discloses a quantitative imaging method and device of magnetic resonance. In the method, a magnetic resonance quantitative value is obtained according to a second deep neural network, the deep neural network as a data driving type model can describe the real world accurately, and compared with a present quantitative imaging mathematical model for calculating the magnetic resonance, the more accurate magnetic resonance quantitative value can be obtained according to the deep neural network model. In addition, the deep neural network runs faster, the computation time for the magnetic resonance quantitative value can be reduced, and the obtaining efficiency is improved. Input data of the second deep neural network model includes a reconstructed image, and the image reconstruction method via the deep neural network is higher in the image reconstruction rate. Thus, the image reconstruction method helps improving the quantitative imaging speed of magnetic resonance.

Description

technical field [0001] The present application relates to the technical field of medical imaging, in particular to a magnetic resonance quantitative imaging method and device. Background technique [0002] Magnetic resonance imaging (Magnetic Resonance Imaging, MRI), as a multi-parameter, multi-contrast imaging technology, is one of the main imaging methods in modern medical imaging, which can reflect various characteristics such as tissue T1, T2 and proton density. Provide information for disease detection and diagnosis. [0003] Traditional MRI images mainly consist of qualitative images of different contrast properties such as T 1 Weighted, T 2 weighting, proton density weighting, diffusion weighting, susceptibility weighting and more. But MRI images can provide far more than these qualitative information, it can also provide MRI quantitative information. The MRI quantitative information is more important for disease diagnosis, especially in brain neuroscience researc...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01R33/561G01R33/48
CPCG01R33/4818G01R33/5611
Inventor 黄峰
Owner SHANGHAI NEUSOFT MEDICAL TECH LTD
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