Wavelet smoothing of functional magnetic resonance images: a preliminary report
Bradley J. Lucier · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2003
Functional (time-dependent) Magnetic Resonance Imaging can be used to determine which parts of the brain are active during various limited activities; these parts of the brain are called activation regions. In this preliminary study we describe some experiments that are suggested from the following questions: Does one get improved results by analyzing the complex image data rather than just the real magnitude image data? Does wavelet shrinkage smoothing improve images? Should one smooth in time as well as within and between slices? If so, how should one model the relationship between time smoothness (or correlations) and spatial smoothness (or correlations). The measured data is really the Fourier coefficients of the complex image---should we remove noise in the Fourier domain before computing the complex images? In this preliminary study we describe some experiments related to these questions.