title: A new distortion model for strong inhomogeneity problems in echo-planar MRI.
abstract: This paper proposes a new distortion model for strong inhomogeneity problems in echo planar imaging (EPI). Fast imaging sequences in magnetic resonance imaging (MRI), such as EPI, are very important in applications where temporal resolution or short total acquisition time is essential. Unfortunately, fast imaging sequences are very sensitive to variations in the homogeneity of the main magnetic field. The inhomogeneity leads to geometrical distortions and intensity changes in the image reconstructed via fast Fourier transform. Also, under strong inhomogeneity, the accelerated intravoxel dephase may overly attenuate signals coming from regions with higher inhomogeneity variations. Moreover, coarse discretization schemes for the inhomogeneity are not able to cope with this problem, producing discretization artifacts when large inhomogeneity variations occur. Most of the existing models do not attempt to solve this problem. In this paper, we propose a modification of the discrete distortion model to incorporate the effects of the intravoxel inhomogeneity and to minimize the discretization artifacts. As a result, these problems are significantly reduced. Extensive experiments are shown to demonstrate the achieved improvements. Also, the performance of the new model is evaluated for conjugate phase, least squares method (minimized iteratively using conjugated gradients), and regularized methods (using a total variation penalty).
authors.affiliation: Federal University of Technology-Paraná (UTFPR), 80230-901 Curitiba, Brazil. marcelozibetti@utfpr.edu.br
authors.forename: Marcelo V W
authors.initials: MV
authors.lastname: Zibetti
authors.forename: Alvaro R
authors.initials: AR
authors.lastname: De Pierro
mesh_terms: D000465:Algorithms; D017352:Echo-Planar Imaging / Q000379:methods*; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D016018:Least-Squares Analysis; D008962:Models, Theoretical; D019047:Phantoms, Imaging; D013997:Time Factors