STATISTICAL-METHODS IN THE FOURIER DOMAIN TO ENHANCE AND CLASSIFY IMAGES

A mathematical model, for which rigorous methods of statistical infere nce are available, is described and techniques for image enhancement a nd linear discriminant analysis of groups are developed. Since the gra y values of neighboring pixels in tomographically produced medical ima ges are spatially correlated, the calculations are carried out in the Fourier domain to insure statistical independence of the variables. Fu rthermore, to increase the power of statistical tests the known spatia l covariance was used to specify constraints in the spectral domain. T hese methods were compared to statistical procedures carried out in th e spatial domain. Positron emission tomography (PET) images of alcohol ics with organic brain disorders were compared by these techniques to age-matched normal volunteers. Although these techniques are employed to analyze group characteristics of functional images, they provide a comprehensive set of mathematical and statistical procedures in the sp ectral domain that on also be applied to images of other modalities, s uch as computed tomography (CT) or magnetic resonance imaging(MRI). (C ) 1996 Academic Press, Inc.