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A multi-contrast MRI image reconstruction method based on deep learning

A deep learning and image reconstruction technology, applied in image data processing, 2D image generation, instruments, etc., can solve problems such as the inability to guarantee the effect of MRI image reconstruction, and achieve the effect of improving reconstruction quality and ensuring accuracy and reliability.

Active Publication Date: 2022-04-19
GUANGDONG UNIV OF TECH
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Problems solved by technology

[0006] In order to solve the problem that the current MRI image reconstruction method cannot guarantee the MRI image reconstruction effect under multi-contrast ratios, the present invention proposes a multi-contrast MRI image reconstruction method based on deep learning to improve the reconstruction quality of MRI images and ensure the accuracy and accuracy of the diagnostic results of the medical system. reliability

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  • A multi-contrast MRI image reconstruction method based on deep learning
  • A multi-contrast MRI image reconstruction method based on deep learning
  • A multi-contrast MRI image reconstruction method based on deep learning

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Embodiment 1

[0058] The positional relationship described in the drawings is only for illustrative purposes and cannot be construed as a limitation to this patent;

[0059] Such as figure 1 The flow chart of the multi-contrast MRI image reconstruction method based on deep learning shown in figure 1 , the steps of the method include:

[0060] A multi-contrast MRI image reconstruction method based on deep learning, at least comprising:

[0061] S1. Collect real full-sampled MRI images to form the real labels of the training set as supervision, and use the training set samples to train a deep convolutional neural network Convnet(·);

[0062] S2. Put T 1 The contrast undersampled MRI image is used as the input of the deep convolutional neural network Convnet( ), and the output T 1 Contrast initially fully sampled MRI images; the T 2 The contrast undersampled MRI image is used as the input of the deep convolutional neural network Convnet( ), and the output T 2 Contrast initially fully sam...

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Abstract

The present invention proposes a multi-contrast MRI image reconstruction method based on deep learning, which relates to the technical field of medical image processing. The training set samples are composed of real full-sampled MRI images and reconstructed MRI images randomly sampled in K space. Train a deep convolutional neural network, then use under-sampled MRI images with different contrasts as its input, and output preliminary full-sampled MRI images with different contrasts. The encoder extracts the structural features and contrast features of the preliminary full-sampled MRI images with different contrasts. Constraints, finally generate the final complete MRI images with different contrasts through the generator, overcome most current models that only use single-contrast MRI images for reconstruction, and lack the use of multi-contrast MRI image correlation information for reconstruction, and improve the MRI image Reconstruct the quality to ensure the reliability of the diagnostic results of the medical system.

Description

technical field [0001] The present invention relates to the technical field of medical image processing, and more specifically, to a multi-contrast MRI image reconstruction method based on deep learning. Background technique [0002] Magnetic Resonance Imaging (MRI for short) is an important and widely used medical imaging technique, which can be used for imaging the internal structure of the human body. Usually 1R scanning can obtain images with different contrasts, such as T1 and T2 contrasts. In actual diagnosis, doctors need to combine complete MRI images with multiple contrasts for disease diagnosis. Therefore, multiple long-term scans are required for the patient, but the scanning time is increased. Not only will it cause discomfort to the patient, but it may also introduce motion artifacts and reduce the efficiency of MRI use; and reducing the scan time will reduce the amount of data collected, which in turn will lead to a decline in the quality of MRI images, which i...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T11/00G06N3/04
Inventor 蔡越罗玉凌捷柳毅
Owner GUANGDONG UNIV OF TECH
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