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Off‐resonance artifacts correction with convolution in k ‐space (ORACLE)
Author(s) -
Lin Wei,
Huang Feng,
Simonotto Enrico,
Duensing George R.,
Reykowski Arne
Publication year - 2012
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.23135
Subject(s) - k space , kernel (algebra) , convolution (computer science) , fourier transform , artifact (error) , computer science , imaging phantom , artificial intelligence , algorithm , physics , mathematics , optics , mathematical analysis , artificial neural network , combinatorics
Abstract Off‐resonance artifacts hinder the wider applicability of echo‐planar imaging and non‐Cartesian MRI methods such as radial and spiral. In this work, a general and rapid method is proposed for off‐resonance artifacts correction based on data convolution in k ‐space. The acquired k ‐space is divided into multiple segments based on their acquisition times. Off‐resonance‐induced artifact within each segment is removed by applying a convolution kernel, which is the Fourier transform of an off‐resonance correcting spatial phase modulation term. The field map is determined from the inverse Fourier transform of a basis kernel, which is calibrated from data fitting in k ‐space. The technique was demonstrated in phantom and in vivo studies for radial, spiral and echo‐planar imaging datasets. For radial acquisitions, the proposed method allows the self‐calibration of the field map from the imaging data, when an alternating view‐angle ordering scheme is used. An additional advantage for off‐resonance artifacts correction based on data convolution in k ‐space is the reusability of convolution kernels to images acquired with the same sequence but different contrasts. Magn Reson Med, 2011. © 2011 Wiley Periodicals, Inc.