Reconstruction method and system for magnetic resonance parameter quantitative imaging

Abstract

The invention relates to the field of magnetic resonance, in particular to a reconstruction method and system for magnetic resonance parameter quantitative imaging, and the method comprises the following steps: obtaining full-sampling K space data; obtaining a corresponding reference full-sampling weighted image; obtaining training input data; inputting the training input data into a reconstruction module to obtain a first weighted image; a reconstruction module is optimized based on the calculation operation of the first weighted image and the reference full-sampling weighted image; acquiring a second weighted image based on the first weighted data input generation module; a calculation operation optimization generation module based on the second weighted image and the reference full-sampling weighted image; obtaining a target neural network based on the operation of simultaneously optimizing the reconstruction module and the generation module; obtaining target under-sampling K space data and defining the target under-sampling K space data as target input data; obtaining a target weighted image based on the target input data; and obtaining a target quantitative parameter image corresponding to the target weighted image. The method has the effect of realizing rapid and accurate magnetic resonance parameter imaging.

Description

technical field [0001] The present application relates to the field of magnetic resonance, in particular to a reconstruction method and system for quantitative imaging of magnetic resonance parameters. Background technique [0002] Magnetic resonance imaging technology, as a complex non-invasive detection technology, can provide rich information on various tissues inside the human body, and display anatomical and pathological cross-sectional images of different human body structures in different grayscales. Compared with CT imaging technology, magnetic resonance imaging technology has the advantages of no ionizing radiation and high soft tissue contrast. Different tissues of the human body can be distinguished by magnetic resonance imaging. The difference in image signals comes from different parameters of the tissue itself, such as longitudinal relaxation time (T1), transverse relaxation time (T2), and proton density (PD). In clinical applications, the parameter setting of...

AI Technical Summary

Problems solved by technology

[0003] However, due to the need to acquire multiple weighted images for quantitative imaging, the imaging time is equal to the imaging time of a single scan multiplied by the number of contrasts that need to be acquired. Among them, the long imaging time of a single scan will cause image motion artifacts, while multiple The movement of the patient's limbs between scans will cause displacements between different contrast-weighted images, resulting in errors in the fitted parameter values, interfering with the doctor's diagnosis, and multiplying the total scan time for parametric imaging

Images