Normalization of Functional Magnetic Resonance Images by Classified Cerebrospinal Fluid Cluster
For functional magnetic resonance imaging (fMRI) time series data, traditional intensity normalization techniques may introduce negative correlation with the neurological stimulation in non-activated voxels, and hence may cause incorrect identification of the activated/deactivated region. In this study, we present a modified proportional scaling method for intensity normalization using segmented specific tissue. In particular, the mean intensity across the classified cerebrospinal fluid (CSF) cluster, instead of the one across the entire intracerebral voxels, is used for the rescaling of all voxel intensity of a particular image frame. The usefulness of the method is demonstrated on block design fMRI data, which shows that the approach can avoid the negative shift in Z statistics quite well. In addition, this strategy can also be applicable to the analysis of positron emission tomography (PET), single photon emission computed tomography (SPECT) and other functional imaging modalities