Eddy current correction method and device, mobile terminal and readable storage medium

Abstract

The invention is suitable for and belongs to the field of magnetic resonance sequence design, and provides an eddy current correction method and device, a mobile terminal and a readable storage medium. The method includes the following steps: S1, using a bipolar readout gradient echo sequence to collect a multi-echo image; S2, estimating the first-order phase coefficient of an additional phase term introduced by eddy current in the collected multi-echo image; S3, removing the estimated first-order phase coefficient, and estimating the zero-order phase coefficient of the additional phase term introduced by eddy current in the collected multi-echo image; and S4, removing the error of the additional phase term introduced by eddy current according to the estimated first-order phase coefficientand the estimated zero-order phase coefficient. Through the eddy current correction method provided by the invention, the phase error caused by eddy current in the collected image can be removed, andthe correctness of the result of a subsequent water-fat separation algorithm can be ensured.

Description

technical field [0001] The invention belongs to the field of magnetic resonance sequence design, and in particular relates to an eddy current correction method, device, mobile terminal and readable storage medium. Background technique [0002] Magnetic resonance imaging-based hydrolipid separation or fat quantification has important clinical implications. Multi-echo gradient echo (Gradient Recalled Echo, GRE) sequence is the most common magnetic resonance imaging sequence for water and lipid separation. In this sequence, in order to reduce the echo spacing and repetition period, bipolar readout gradients are usually used to acquire multi-echo images. The echo data did not satisfy the theoretical water-fat mixing model, which led to the failure of the subsequent water-fat separation algorithm based on the complex model. [0003] Specifically, the theoretical water-fat mixing model containing two components (commonly water and fat) is: [0004] [0005] Among them, S n ...

AI Technical Summary

Problems solved by technology

But magnitude fitting is sensitive to noise and to fat model errors

[0016] In summary, none of the solutions provided by the existing technology can simply and efficiently remove the phase error caused by eddy currents in the collected multi-echo images, and thus cannot guarantee the correctness of the results of the water-fat separation algorithm

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