Abstract:
There has been an exponential growth in brain
mapping studies in the past decade using functional MRI (fMRI).
Apart from simple fMRI studies from a single site (scanner),
multi-site studies are gaining great attention, as it has the
potential to provide more data for brain mapping studies,
thereby increasing the statistical power of the brain mapping
studies. Major limitations with the multi-center studies are the
diversity in acquisition and analysis methods, which affect the
imaging results. This study aims at finding a suitable standard
reference map for the sensori-motor fMRI task for the multisite
fMRI data. After the construction of a suitable imaginary
standard reference map, the study further tries to reduce the
inter-scanner differences in multi-center fMRI data by using
correction functions. It is observed that the median images (an
imaginary reference image) work as a good reference map, than
the reference images selected from the data set. A simple linear
regression based correction estimate to the new reference map
is seen to improve the classification accuracy of the functional
activation maps, thus reducing the inter-scanner variability in
multi-site fMRI data.
