Title :
Conjugate phase MRI reconstruction with spatially variant sample density correction
Author :
Noll, Douglas C. ; Fessler, Jeffrey A. ; Sutton, Bradley P.
Author_Institution :
Dept. of Biomed. Eng., Univ. of Michigan, Ann Arbor, MI, USA
fDate :
3/1/2005 12:00:00 AM
Abstract :
A new image reconstruction method to correct for the effects of magnetic field inhomogeneity in non-Cartesian sampled magnetic resonance imaging (MRI) is proposed. The conjugate phase reconstruction method, which corrects for phase accumulation due to applied gradients and magnetic field inhomogeneity, has been commonly used for this case. This can lead to incomplete correction, in part, due to the presence of gradients in the field inhomogeneity function. Based on local distortions to the k-space trajectory from these gradients, a spatially variant sample density compensation function is introduced as part of the conjugate phase reconstruction. This method was applied to both simulated and experimental spiral imaging data and shown to produce more accurate image reconstructions. Two approaches for fast implementation that allow the use of fast Fourier transforms are also described. The proposed method is shown to produce fast and accurate image reconstructions for spiral sampled MRI.
Keywords :
biomedical MRI; fast Fourier transforms; image reconstruction; medical image processing; conjugate phase MRI reconstruction; fast Fourier transforms; image reconstruction; k-space trajectory; magnetic field inhomogeneity; nonCartesian sampled magnetic resonance imaging; phase accumulation; spatially variant sample density compensation function; spatially variant sample density correction; spiral imaging data; Fast Fourier transforms; Fourier transforms; Image reconstruction; Magnetic domains; Magnetic fields; Magnetic resonance imaging; Nonuniform electric fields; Phase distortion; Reconstruction algorithms; Spirals; Image reconstruction; magnetic field inhomogeneity; magnetic resonance imaging; spiral imaging; Algorithms; Anisotropy; Artifacts; Artificial Intelligence; Brain; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Magnetic Resonance Imaging; Models, Biological; Models, Statistical; Phantoms, Imaging; Reproducibility of Results; Sensitivity and Specificity;
Journal_Title :
Medical Imaging, IEEE Transactions on
DOI :
10.1109/TMI.2004.842452