An Adaptive Highly Undersampled Hyperpolarized Gas Lung Dynamic MRI Reconstruction Method

An undersampling and self-adaptive technology, applied in applications, medical science, diagnosis, etc., can solve the problems of inability to meet the needs of adaptive high-undersampling K-space data reconstruction, reconstruction results artifacts, etc., to achieve low reconstruction error, increase imaging Speed, the effect of ensuring image quality

Active Publication Date: 2020-06-19
WUHAN INST OF PHYSICS & MATHEMATICS CHINESE ACADEMY OF SCI
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Problems solved by technology

However, these methods cannot meet the needs of adaptive high undersampling K-space data reconstruction, resulting in obvious artifacts in the reconstruction results

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  • An Adaptive Highly Undersampled Hyperpolarized Gas Lung Dynamic MRI Reconstruction Method
  • An Adaptive Highly Undersampled Hyperpolarized Gas Lung Dynamic MRI Reconstruction Method
  • An Adaptive Highly Undersampled Hyperpolarized Gas Lung Dynamic MRI Reconstruction Method

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Embodiment 1

[0029] In this embodiment, the hyperpolarized gas is 129 Xe.

[0030] An adaptive high undersampling hyperpolarized gas lung dynamic MRI reconstruction method, comprising the following steps:

[0031] Step 1. Obtain M frames of K-space data d of the existing full-sampled hyperpolarized gas lung dynamic image 1 , set the minimum value TH=10% of the undersampling rate SR, and in this embodiment, M is 15.

[0032] Step 2. Perform undersampling on the K-space data of the first frame to the K-space data of the fifteenth frame according to the corresponding under-sampling rate of the K-space of the first frame to the under-sampling rate of the K-space of the fifteenth frame to obtain the under-sampled K-space data of the first frame From the undersampled K-space data of the 15th frame, the undersampled K-space data of the 1st frame to the 15th frame of the undersampled K-space data are reconstructed by the CS reconstruction algorithm and the reconstruction error is evaluated, and ...

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Abstract

The invention discloses a method for reconstructing a hyperpolarized gas lung dynamic MRI by adopting self-adaptive high-rate undersampling. The method comprises the following steps: optimizing the Kspace undersampling rate of each frame according to the K space data of the existing hyperpolarized gas lung dynamic image; according to the optimized K space undersampling rate, generating an undersampling track, and carrying out lung inspiration dynamic imaging, thus obtaining undersampling K space data; and reconstructing the hyperpolarized gas lung dynamic magnetic resonance image by utilizingthe undersampling K space data and a reconstruction objective function. With the method, the hyperpolarized gas lung dynamic magnetic resonance image with high time resolution and rich detailed information can be obtained.

Description

technical field [0001] The present invention relates to the fields of lung magnetic resonance imaging (Magnetic resonance imaging, MRI) technology, undersampling and compressed sensing (Compressed sensing, CS) theory, etc., and specifically relates to an adaptive high undersampling hyperpolarized gas dynamic MRI reconstruction of the lungs method. Background technique [0002] Hyperpolarized gas lung MRI is an emerging lung imaging method that enables effective assessment of lung ventilatory function (eg, air-air exchange, air-blood exchange) [M.S.Albert et al. Nature, 1994, 370: 199-201.], has great potential in the early diagnosis of major lung diseases [such as chronic obstructive pulmonary disease (Chronic obstructive pulmonary disease, COPD), asthma, etc.] [F.C.Horn et al.Radiology, 2017, 284: 854-861.]. [0003] The commonly used hyperpolarized gas lung MRI is to image the lungs in a breath-hold state to obtain static images, such as ventilation images and diffusion-...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): A61B5/055
CPCA61B5/055
Inventor 周欣肖洒邓鹤段曹辉孙献平叶朝辉
Owner WUHAN INST OF PHYSICS & MATHEMATICS CHINESE ACADEMY OF SCI
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