MULTI-EXCITATION DIFFUSION-WEIGHTED MAGNETIC RESONANCE IMAGING METHOD BASED ON DATA CONSISTENCY

摘要

A multi-excitation diffusion-weighted magnetic resonance imaging method based on data consistency comprises: acquiring multi-channel pre-scan data; generating, according to the multi-channel pre-scan data, a convolution kernel based on data consistency; acquiring diffusion-weighted magnetic resonance imaging data of multiple excitations; calculating reconstructed data according to the convolution kernel and the diffusion-weighted magnetic resonance imaging data of each excitation; combining the reconstructed data to obtain a combined image; updating the combined image to obtain an updated image; checking whether iteration has reached a predetermined condition; and if the iteration reaches the predetermined condition, ending the iteration; or if the iteration has not reached the predetermined condition, performing phase recovery on the updated image. The method improves the efficiency of image sampling, and obtains a relatively stable reconstructed image.