公开(公告)号：US20190331750A1

公开(公告)日：2019-10-31

申请号：US15965763

申请日：2018-04-27

Applicant: General Electric Company

Inventor： Quan Zhu ,  Gaohong Wu ,  Shaorong Chang ,  Richard Hinks

IPC: G01R33/565 ,  G01R33/563

Abstract: Various methods and systems are provided for ghost artifact reduction in magnetic resonance imaging (MRI). In one embodiment, a method for an MRI system comprises acquiring a non-phase-encoded reference dataset, calculating phase corrections for spatial orders higher than first order from the non-phase-encoded reference dataset, acquiring a phase-encoded k-space dataset, correcting the phase-encoded k-space dataset with the phase corrections, and reconstructing an image from the corrected phase-encoded k-space dataset. In this way, ghost artifacts caused by phase errors during EPI may be substantially reduced, thereby improving image quality especially when imaging with a large field of view.

公开(公告)号：US10690741B2

公开(公告)日：2020-06-23

申请号：US15965763

申请日：2018-04-27

Applicant: General Electric Company

Inventor： Quan Zhu ,  Gaohong Wu ,  Shaorong Chang ,  Richard Hinks

IPC: G01R33/565 ,  G01R33/563

Abstract: Various methods and systems are provided for ghost artifact reduction in magnetic resonance imaging (MRI). In one embodiment, a method for an MRI system comprises acquiring a non-phase-encoded reference dataset, calculating phase corrections for spatial orders higher than first order from the non-phase-encoded reference dataset, acquiring a phase-encoded k-space dataset, correcting the phase-encoded k-space dataset with the phase corrections, and reconstructing an image from the corrected phase-encoded k-space dataset. In this way, ghost artifacts caused by phase errors during EPI may be substantially reduced, thereby improving image quality especially when imaging with a large field of view.