Sequential anisotropic Wiener filtering applied to 3D MRI data.
We present three different sequential Wiener filters, namely, isotropic, orientation and anisotropic. The first one is similar to the classical Wiener filter in the sense that it uses an isotropic neighborhood to estimate its parameters. Here we present a sequential version of it. The orientation Wiener filter uses oriented neighborhoods to estimate the structure orientation present at each voxel, giving rise to a modified estimator of the parameters. Finally, the anisotropic Wiener filter combines both approaches adaptively so that the appropriate approach is locally selected. Several synthetic experiments are presented showing the performance of the filters with respect to their parameters. A mean square error analysis is performed using a publicly available magnetic resonance imaging (MRI) brain phantom and a comparison with other filtering approaches is carried out. In addition, results from filtering real MRI data are presented.
Martin-Fernandez
Marcos
M
Laboratory of Mathematics in Imaging (LMI), Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA. marcma@tel.uva.es
Alberola-Lopez
Carlos
C
Ruiz-Alzola
Juan
J
Westin
Carl-Fredrik
CF
D000465:Algorithms; D016880:Anisotropy; D001499:Bayes Theorem; D001931:Brain Mapping / Q000379:methods*; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional; D008279:Magnetic Resonance Imaging / Q000379:methods*; D019047:Phantoms, Imaging