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Quick magnetic resonance imaging method based on recursive residual U-type network

A magnetic resonance imaging and network technology, applied in the fields of medical science, diagnosis, diagnosis recording/measurement, etc., can solve the problems such as patents or articles that have not appeared in rapid MRI imaging

Active Publication Date: 2019-08-23
HANGZHOU DIANZI UNIV
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Problems solved by technology

[0006] The above published articles or patents on fast MRI imaging based on deep learning convolutional neural network are mainly based on deep learning method of convolutional neural network or U-shaped network for fast MRI imaging, or based on recursive residual Fast MRI imaging of convolutional neural network, or medical image segmentation based on recursive residual U-shaped network, there is no patent or article on fast MRI imaging based on recursive residual U-shaped network

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  • Quick magnetic resonance imaging method based on recursive residual U-type network
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Embodiment Construction

[0088] The invention includes three steps: data processing, model training, and image reconstruction.

[0089] 1. Data processing

[0090] Data processing consists of two steps: data sampling and zero-filling reconstruction.

[0091] 1-1. Data sampling

[0092] Full sample k-space data is k ref (x k ,y k )(Such as figure 1 (a)), where x k Represents the k-space frequency encoding (Frequency Encoding, FE) direction, y k Indicates the direction of Phase Encoding (PE). Fully sampled k-space data k ref (x k ,y k ) From the fully sampled reference image I ref (x,y) (e.g. figure 1 (b)) Obtained by discrete Fourier transform (DFT).

[0093] k ref (x k ,y k )=DFT(I ref (x,y)) (1)

[0094] For the simulated under-sampling of k-space data, a 1-dimensional uniform under-sampling template mask (such as figure 1 As shown in (c)), data are collected every n rows in the PE direction, 4% rows in the center of the PE direction are collected, and all collected in the FE direction. The sampling p...

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Abstract

The invention discloses a quick magnetic resonance imaging method based on a recursive residual U-type network. The method comprises the three steps of data processing, model training and image reconstruction. By adopting the method, a recursive residual module is added to the U-type network, the problems of gradient blast and gradient vanishing caused by back propagation of the network are solved, new network parameters are not added while the layer number of the network is increased, the quality of a reconstructed image is obviously improved, and more image details can be restored.

Description

Technical field [0001] The invention belongs to the field of magnetic resonance imaging, and relates to a fast magnetic resonance imaging method based on a recursive residual U-shaped network. Background technique [0002] Magnetic Resonance Imaging (MRI) technology is very popular in clinical applications because of its high soft tissue resolution and no ionizing radiation damage to the human body. However, due to the slow imaging speed of MRI, the physiological movement of the examinee during the imaging process often causes imaging artifacts, which are difficult to meet the requirements of real-time imaging. Therefore, how to accelerate the imaging speed of MRI is one of the hot spots in MRI theory and technology research. One. Reducing the total amount of MRI k-space data acquisition is an effective acceleration method, but a large reduction in the amount of data acquisition will bring about a significant decline in image quality, although researchers can use a variety of re...

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Application Information

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IPC IPC(8): A61B5/055
CPCA61B5/055A61B5/7257A61B5/7264
Inventor 曹康慧吴琛艳胡源金朝阳
Owner HANGZHOU DIANZI UNIV
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