ABSTRACT
This chapter discusses the nature of brain imaging data and the way it is processed in the analysis. There are many different types of brain images depending on the equipment and the imaging method. This book focuses on structural and functional magnetic resonance images of the brain. The principles of structural and functional brain imaging are briefly described and the formats in which they are recorded are explained. A structure common to all the discussed modalities is that the three-dimensional image of the brain contains a value representing the characteristics of the brain for each compartment separated by a cube called a voxel. The chapter explains how the brain images are transformed into a dataset in the same format as the one used for general statistical analysis. The chapter also explains how this idea can be applied to other modalities as well. Pre-processing the raw brain image data to derive the data used for statistical analysis is introduced. Particularly, the basic concepts of conversion to the standard brain image for anatomical standardization, reduction or increase in the number of voxels and associated voxel interpolation, smoothing methods for noise reduction, and satisfying the assumptions of the statistical theory are explained using the R codes.
