Magnetic resonance image generation method and system, terminal and storage medium

Abstract

The invention provides a magnetic resonance image generation method and system, a terminal and a storage medium. The method comprises the steps of constructing a magnetic resonance image data set; constructing a convolutional neural network model; using a magnetic resonance image data set to train the convolutional neural network model until a cost function of the neural network converges; and inputting scanning data of a group of magnetic resonance imaging instruments into the trained convolutional neural network model to generate a multi-contrast magnetic resonance imaging result. Through deep learning convolutional neural network model U-Net, multi-contrast magnetic resonance images can be generated from magnetic resonance fingerprints (MRF) scanned in a single sequence, that is, the images with multiple contrast ratios can be generated at a time through scanning. Therefore, not only can the scanning time be greatly reduced, but also the cost of magnetic resonance imaging can be reduced, so that the clinical application of the technology is wider.

Description

technical field [0001] The invention belongs to the technical field of magnetic resonance, and in particular relates to a magnetic resonance image generation method, system, terminal and storage medium. Background technique [0002] MRI (Magnetic Resonance Imaging) is a non-invasive imaging technique that generates detailed three-dimensional images of anatomy without the use of harmful ionizing radiation (compared to X-ray CT), and is commonly used for disease detection, diagnosis, and condition monitoring. It uses radio frequency electromagnetic waves (RF, radio frequency) to excite nuclear substances with non-zero spins placed in a static magnetic field to generate nuclear magnetic resonance (NMR, Nuclear Magnetic Resonance), and uses induction coils to collect magnetic resonance signals. Processing methods for processing and final imaging. [0003] MRI is especially suited for imaging non-skeletal parts, that is, the soft tissues of the body. Unlike computed tomography ...

AI Technical Summary

Problems solved by technology

[0004] Although MRI has many excellent characteristics, the long acquisition time of MRI images greatly limits its clinical application (emergency scan, etc.)

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