Statistical analysis of image differences by wavelet decomposition
The wavelet transform was studied for the analysis of glucose utilization differences between subject groups shown in PET images. To strengthen statistical inference, it was of particular interest investigating the trade-off between signal localization and image decomposition into uncorrelated components. This trade-off is governed by wavelet regularity, and was found to be best for third-order orthogonal spline wavelets. Only about 1.6% of the components were statistically different (p<.05) from noise, constituting a sufficient set to synthesize local image differences by the inverse wavelet transform.<<ETX>>