Selection of Wavelet Based Optimal Denoising Method in fMRI Signals

Functional magnetic resonance images (fMRI) contains high amount of noise due to their structures. This high noise limits the correct interpretation of the information contained in the signal. In order to interpret the data correctly, it is necessary to eliminate the noise with effective and efficient noise reduction techniques while protecting the information in the signal. The aim of this study is to find an optimal methodology for denoising. For this purpose, Cubic Spline, Discrete Wavelet Transform (DWT) and Maximal Overlap Discrete Wavelet Transform (MODWT) are used as wavelet based noise reduction methods. These methods are applied on a real fMRI signal and compared with different parameters and their performance was evaluated.