We present a general wavelet-based denoising scheme for functional neuroimages and compare it to Gaussian smoothing, the standard method in functional neuroimaging. We adapted WaveLab thresholding routines to 2D data, and tested their effect on the signal-to-noise ratio of noisy images. In a simulated time series test, we also investigated the shapes of detected activations after denoising.
|Title of host publication||EPRINTS-BOOK-TITLE|
|Publisher||University of Groningen, Johann Bernoulli Institute for Mathematics and Computer Science|
|Number of pages||6|
|Publication status||Published - 2002|
- signal-to-noise ratio
- functional neuroimaging