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
Functional (time-dependent) Magnetic Resonance Imaging can be used to determine which parts of the b...
Functional magnetic resonance imaging (fMRI) is a recent, non-invasive technique that allows the mea...
There is a growing interest in using multiresolution noise filters in a variety of medical imaging a...
We present a general wavelet-based denoising scheme for functional neuroimages and compare it to Gau...
We present a general wavelet-based denoising scheme for functional neuroimages and compare it to Gau...
We present a general wavelet-based denoising scheme for functional magnetic resonance imaging (fMRI)...
The quality of statistical analyses of functional neuroimages is studied after applying various prep...
The quality of statistical analyses of functional neuroimages is studied after applying various prep...
We present a general wavelet-based denoising scheme for functional magnetic resonance imaging (fMRI)...
We present a general wavelet-based denoising scheme for functional magnetic resonance imaging (fMRI)...
We present a general wavelet-based denoising scheme for functional neuroimages and compare it to Gau...
PURPOSE: To improve the signal-to-noise ratio (SNR) of functional magnetic resonance imaging (fMRI) ...
We propose Wavelet ANOVA, a simple general-purpose statistical method for analysis of signals and im...
The use of the wavelet transform is explored for the detection of differences between brain function...
Objective. Among the different approaches for denoising neural signals, wavelet-based methods are wi...
Functional (time-dependent) Magnetic Resonance Imaging can be used to determine which parts of the b...
Functional magnetic resonance imaging (fMRI) is a recent, non-invasive technique that allows the mea...
There is a growing interest in using multiresolution noise filters in a variety of medical imaging a...
We present a general wavelet-based denoising scheme for functional neuroimages and compare it to Gau...
We present a general wavelet-based denoising scheme for functional neuroimages and compare it to Gau...
We present a general wavelet-based denoising scheme for functional magnetic resonance imaging (fMRI)...
The quality of statistical analyses of functional neuroimages is studied after applying various prep...
The quality of statistical analyses of functional neuroimages is studied after applying various prep...
We present a general wavelet-based denoising scheme for functional magnetic resonance imaging (fMRI)...
We present a general wavelet-based denoising scheme for functional magnetic resonance imaging (fMRI)...
We present a general wavelet-based denoising scheme for functional neuroimages and compare it to Gau...
PURPOSE: To improve the signal-to-noise ratio (SNR) of functional magnetic resonance imaging (fMRI) ...
We propose Wavelet ANOVA, a simple general-purpose statistical method for analysis of signals and im...
The use of the wavelet transform is explored for the detection of differences between brain function...
Objective. Among the different approaches for denoising neural signals, wavelet-based methods are wi...
Functional (time-dependent) Magnetic Resonance Imaging can be used to determine which parts of the b...
Functional magnetic resonance imaging (fMRI) is a recent, non-invasive technique that allows the mea...
There is a growing interest in using multiresolution noise filters in a variety of medical imaging a...