Real-world data sets such as recordings from functional magnetic resonance imaging often possess both spatial and temporal structure. Here, we propose an algorithm including such ...
Fabian J. Theis, Peter Gruber, Ingo R. Keck, Elmar...
Abstract. We propose a two-step approach for the analysis of functional magnetic resonance images, in the context of natural stimuli. In the first step, elements of functional bra...
Jarkko Ylipaavalniemi, Eerika Savia, Ricardo Vig&a...
Functional magnetic resonance imaging (fMRI) has become an exceedingly popular technique for studies of human brain activity. Typically, fMRI is performed with >3-mm sampling, s...
David Ress, Sankari Dhandapani, Sucharit Katyal, C...
Abstract. This paper proposes a new adaptive wavelet-based Magnetic Resonance images denoising algorithm. A Rician distribution for background-noise modelling is introduced and a M...