A nonparametric method for automatic correction of intensity nonuniformity in MRI data.
A novel approach to correcting for intensity nonuniformity in magnetic resonance (MR) data is described that achieves high performance without requiring a model of the tissue classes present. The method has the advantage that it can be applied at an early stage in an automated data analysis, before a tissue model is available. Described as nonparametric nonuniform intensity normalization (N3), the method is independent of pulse sequence and insensitive to pathological data that might otherwise violate model assumptions. To eliminate the dependence of the field estimate on anatomy, an iterative approach is employed to estimate both the multiplicative bias field and the distribution of the true tissue intensities. The performance of this method is evaluated using both real and simulated MR data.
Sled
J G
JG
McConnell Brain Imaging Centre, Montréal Neurological Institute and McGill University, Canada. jgsled@bic.mni.mcgill.ca
Zijdenbos
A P
AP
Evans
A C
AC
D001921:Brain / Q000033:anatomy & histology; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008962:Models, Theoretical