Distributed ultrafast magnetic resonance imaging method and imaging system thereof

Abstract

The invention discloses a distributed ultrafast magnetic resonance imaging method. The method specifically comprises the following steps: step 1, constructing a nuclear magnetic resonance implicit regularization model; 2, performing data acquisition based on the implicit regularization model established in the step 1; and step 3, carrying out standardization processing on the data acquired in the step 2. The invention further discloses a distributed ultrafast magnetic resonance imaging system, a signal acquisition end and an image reconstruction end in magnetic resonance imaging are separated, only a magnetic resonance scanning terminal is deployed in a hospital, an image reconstruction part is deployed in a cloud end, and the cloud end is configured based on implicit regularization. Therefore, high-quality reconstruction of the high-acquisition and under-acquisition magnetic resonance data is realized.

Description

technical field [0001] The invention belongs to the technical field of medical magnetic resonance imaging, relates to a distributed ultrafast magnetic resonance imaging method, and also relates to an imaging system of the above imaging system. Background technique [0002] Magnetic resonance is an important medical imaging device. Compared with medical imaging techniques such as ultrasound, CT and PET, magnetic resonance imaging has rich contrast, better soft tissue resolution and functional imaging capabilities, and no radiation damage. my country has a huge demand for magnetic resonance equipment, but due to the extremely high price of magnetic resonance equipment, the installed capacity of magnetic resonance equipment per million people in my country is only 15, which is only about 1 / 5 of the developed countries. It is rare and cannot benefit the grassroots people in our country. [0003] In addition, limited by the physical principles of imaging, magnetic resonance has ...

AI Technical Summary

Problems solved by technology

my country has a huge demand for magnetic resonance equipment, but due to the extremely expensive price of complete magnetic resonance machines, the installed capacity per million people in my country is only 15, which is only about 1 / 5 of that in developed countries, and the installed capacity in some remote, poor and grassroots areas is even higher It is rare and cannot benefit the grassroots people in our country

[0003] In addition, limited by the physical principles of imaging, magnetic resonance has the disadvantage of slow scanning speed, which limits the promotion of high-end clinical applications

In recent years, new fast magnetic resonance imaging methods have been emerging, but limited by the manufacturer's platform, the new fast magnetic resonance imaging methods cannot be integrated into magnetic resonance equipment, which limits the application of new technologies, and patients cannot enjoy the benefits brought by new technologies. Easy to scan

[0004] The main reason for the above problems is that the existing magnetic resonance is an integrated design, that is, the magnetic resonance equipment integrates the dual functions of signal acquisition (scanning end) and image reconstruction, resulting in expensive equipment, and equipment manufacturers control all decision-making power. The disadvantages of having integrated MRI are as follows:

[0005] 1. At present, the MRI in the hospital is all integrated design, that is, the MRI equipment itself undertakes multiple tasks such as signal acquisition, image reconstruction, and some post-analysis, and the cost of corresponding scanning hardware, reconstruction workstation, and analysis computer is very high. There are many software and hardware, and the overall purchase and maintenance costs are extremely expensive

[0006] 2. Since magnetic resonance equipment belongs to different manufacturers, each company has different hardware performance, data preprocessing methods, image reconstruction algorithms and other standards, resulting in different image quality, resulting in subsequent diagnosis, especially intelligent diagnosis, which depends on equipment manufacturers, and it is difficult to establish a unified judging criteria and methods

The update of the reconstruction algorithm depends on the manufacturer, the iteration cycle is very long, and the patient cannot enjoy the scanning convenience brought by the new technology

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