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Computed tomography (CT) image reconstruction method based on magnetic resonance imaging (MRI)

A technology of CT images and magnetic resonance images, applied in the field of CT image reconstruction based on MRI, can solve the problems of poor display of fine lung structures and slow MRI imaging speed, and achieve the advantages of avoiding ionizing radiation, fast imaging speed and wide application range Effect

Active Publication Date: 2020-07-24
ZHEJIANG UNIV
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Problems solved by technology

[0003] In view of this, the present invention provides an MRI-based CT image reconstruction method with fast imaging speed and good display effect on the fine structure of the lungs, aiming at the above-mentioned problems of slow MRI imaging speed and poor display of the fine structure of the lungs

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  • Computed tomography (CT) image reconstruction method based on magnetic resonance imaging (MRI)
  • Computed tomography (CT) image reconstruction method based on magnetic resonance imaging (MRI)
  • Computed tomography (CT) image reconstruction method based on magnetic resonance imaging (MRI)

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Embodiment Construction

[0054] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments, but the present invention is not limited to these embodiments. The present invention covers any alternatives, modifications, equivalent methods and schemes made on the spirit and scope of the present invention. In order to provide the public with a thorough understanding of the present invention, specific details are set forth in the following preferred embodiments of the present invention, but those skilled in the art can fully understand the present invention without the description of these details.

[0055] Compared with traditional MRI image reconstruction techniques, image reconstruction methods based on deep learning have great potential in shortening MRI scan time, speeding up imaging speed, and improving imaging quality. figure 1 It is a flow chart of MRI reconstruction using deep learning network for the present invention. In the proc...

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Abstract

The invention discloses a computed tomography (CT) image reconstruction method based on magnetic resonance imaging (MRI). The CT image reconstruction method comprises the following steps: 1) reconstructing MRI by using a deep learning network, training the deep learning network, acquiring undersampling k spatial data of a to-be-detected object, and inputting the undersampling k spatial data of theto-be-detected object in the trained deep learning network to acquire online MRI of the to-be-detected object; and 2) using a bidirectional generative adversarial network to reconstruct a CT image through MRI. The CT image reconstruction method has the following advantages: (1) the MRI imaging speed is high; (2) the method has wide application ranges and can be applied to imaging of other parts of a human body as well as imaging of the lung; (3) the CT image is obtained through MRI reconstruction, and ionizing radiation of CT examination is avoided; and (4) the CT image obtained through reconstruction can also be used for radiotherapy plan formulation and PET attenuation correction.

Description

technical field [0001] The invention relates to the technical field of medical image processing, in particular to an MRI-based CT image reconstruction method. Background technique [0002] COVID-19 is highly contagious and has a high fatality rate. Early detection, early diagnosis, early treatment, and early isolation are currently the most effective means of prevention and treatment. Compared with various limitations of nucleic acid examination, CT (computed tomography) examination is timely, accurate, fast, with a high positive rate, and the extent of lung lesions is closely related to clinical symptoms. Therefore, it has become the main reference for early screening and diagnosis of patients with new coronavirus pneumonia in accordance with. According to the diagnosis and treatment plan for novel coronavirus pneumonia (Trial Sixth Edition), multiple small patchy shadows and interstitial changes appeared in the early stage of new coronary pneumonia, especially in the extr...

Claims

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Application Information

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IPC IPC(8): A61B5/055A61B5/00A61B6/03A61N5/10G06F17/14G06N3/04G06N3/08G06T11/00
CPCG06N3/08G06T11/005G06T5/10A61B6/5247G06T2207/10081G06T2207/10088G06T2207/20056G06T2207/20081G06T2207/20084G06N3/044
Inventor 张鞠成孙云饶先成孙建忠
Owner ZHEJIANG UNIV
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