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Spatially dependent filtering for removing phase distortions at the cortical surface
Author(s) -
Ng Amanda,
Johnston Leigh,
Chen Zhaolin,
Cho ZangHee,
Zhang Jingxin,
Egan Gary
Publication year - 2011
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.22825
Subject(s) - phase (matter) , computer science , artificial intelligence , computer vision , surface (topology) , gaussian , signal (programming language) , field (mathematics) , pattern recognition (psychology) , physics , mathematics , geometry , quantum mechanics , pure mathematics , programming language
Recent advances in high field magnetic resonance technology have increased the interest in the phase of the complex data. Processed phase images are derived from the phase signal by removing the bias field and phase wraps from the initial data. However, the usefulness of this data has been hindered by artifacts at the brain/non‐brain surface, particularly in cortical regions. A method is proposed that efficiently removes surface artifacts by performing Gaussian filtering with spatially varying parameters of unwrapped or complex filtered phase images. The proposed method is shown to produce improved images, revealing underlying structure and detail that are otherwise obscured by surface artifacts in images produced by traditional phase processing methods. Magn Reson Med, 2011. © 2011 Wiley‐Liss, Inc.