Publications related to Statistical Analysis of Functional MRI Data in the Wavelet Domain

Hydrological model performance and parameter estimation in the wavelet-domain

This paper proposes a method for rainfall-runoff model calibration and performance analysis in the wavelet-domain by fitting the estimated wavelet-power spectrum (a representation of the time-varying frequency content of a time series) of a simulated disch ...

European Geosciences Union2009

Multi-Lead Wavelet-Based ECG Delineation on a Wearable Embedded Sensor Platform

David Atienza Alonso, Francisco Javier Rincon Vallejos, Nadia Khaled, Nicolas Boichat

This work is dedicated to the sensible optimization and porting of a multi-lead (ML) wavelet-transform (WT)-based electrocardiogram (ECG) wave delineator to a state-of-the-art commercial wearable embedded sensor platform with limited processing and storage ...

2009

False Discovery Rate for Wavelet-Based Statistical Parametric Mapping

Michaël Unser, Dimitri Nestor Alice Van De Ville

Model-based statistical analysis of functional magnetic resonance imaging (fMRI) data relies on the general linear model and statistical hypothesis testing. Due to the large number of intracranial voxels, it is important to deal with the multiple compariso ...

IEEE2008

The Pairing of a Wavelet Basis With a Mildly Redundant Analysis via Subband Regression

Michaël Unser, Dimitri Nestor Alice Van De Ville

A distinction is usually made between wavelet bases and wavelet frames. The former are associated with a one-to-one representation of signals, which is somewhat constrained but most efficient computationally. The latter are over-complete, but they offer ad ...

Institute of Electrical and Electronics Engineers2008

The Monogenic Riesz-Laplace Wavelet Transform

Michaël Unser, Dimitri Nestor Alice Van De Ville, Katarina Balac

We introduce a family of real and complex wavelet bases of

L _{ 2 }

(\mathbb{R} ^{ 2 }

) that are directly linked to the Laplace and Riesz operators. The crucial point is that the family is closed with respect to the Riesz transform which maps a re ...

EURASIP2008

Dynamic PET Reconstruction Using Wavelet Regularization with Adapted Basis Functions

Michaël Unser, Dimitri Nestor Alice Van De Ville, Ildar Khalidov

Tomographic reconstruction from positron emission tomography (PET) data is an ill-posed problem that requires regularization. An attractive approach is to impose an

\ell_{ 1 }

-regularization constraint, which favors sparse solutions in the wavelet dom ...

Institute of Electrical and Electronics Engineers2008

Innovation modelling and wavelet analysis of fractal processes in bio-imaging

Michaël Unser, Dimitri Nestor Alice Van De Ville, Pouya Dehghani Tafti

Growth and form in biology are often associated with some level of fractality. Fractal characteristics have also been noted in a number of imaging modalities. These observations make fractal modelling relevant in the context of bio-imaging. ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2008

WSPM: Wavelet-Based Statistical Parametric Mapping

Michaël Unser, Dimitri Nestor Alice Van De Ville, Thierry Blu

Recently, we have introduced an integrated framework that combines wavelet-based processing with statistical testing in the spatial domain. In this paper, we propose two important enhancements of the framework. First, we revisit the underlying paradigm; i. ...

Elsevier2007

Wavelet-Based Multi-Resolution Statistics for Optical Imaging Signals: Application to Automated Detection of Odour Activated Glomeruli in the Mouse Olfactory Bulb

Michaël Unser, Dimitri Nestor Alice Van De Ville, Thierry Blu

Optical imaging techniques offer powerful solutions to capture brain networks processing in animals, especially when activity is distributed in functionally distinct spatial domains. Despite the progress in imaging techniques, the standard analysis procedu ...

Elsevier2007

Activelets and sparsity: A new way to detect brain activation from fMRI data - art. no. 67010Y

Michaël Unser, Dimitri Nestor Alice Van De Ville, Ildar Khalidov

FMRI time course processing is traditionally performed using linear regression followed by statistical hypothesis testing. While this analysis method is robust against noise, it relies strongly on the signal model. In this paper, we propose a non-parametri ...

Spie-Int Soc Optical Engineering, Po Box 10, Bellingham, Wa 98227-0010 Usa2007

Statistical Analysis of Functional MRI Data in the Wavelet Domain

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Hydrological model performance and parameter estimation in the wavelet-domain

Multi-Lead Wavelet-Based ECG Delineation on a Wearable Embedded Sensor Platform

False Discovery Rate for Wavelet-Based Statistical Parametric Mapping

The Pairing of a Wavelet Basis With a Mildly Redundant Analysis via Subband Regression

The Monogenic Riesz-Laplace Wavelet Transform

Dynamic PET Reconstruction Using Wavelet Regularization with Adapted Basis Functions

Innovation modelling and wavelet analysis of fractal processes in bio-imaging

WSPM: Wavelet-Based Statistical Parametric Mapping

Wavelet-Based Multi-Resolution Statistics for Optical Imaging Signals: Application to Automated Detection of Odour Activated Glomeruli in the Mouse Olfactory Bulb

Activelets and sparsity: A new way to detect brain activation from fMRI data - art. no. 67010Y

Innovation modelling and wavelet analysis of fractal processes in bio-imaging

The Pairing of a Wavelet Basis With a Mildly Redundant Analysis via Subband Regression

Multi-Lead Wavelet-Based ECG Delineation on a Wearable Embedded Sensor Platform

False Discovery Rate for Wavelet-Based Statistical Parametric Mapping

WSPM: Wavelet-Based Statistical Parametric Mapping

Hydrological model performance and parameter estimation in the wavelet-domain

Dynamic PET Reconstruction Using Wavelet Regularization with Adapted Basis Functions

The Monogenic Riesz-Laplace Wavelet Transform

Activelets and sparsity: A new way to detect brain activation from fMRI data - art. no. 67010Y

Wavelet-Based Multi-Resolution Statistics for Optical Imaging Signals: Application to Automated Detection of Odour Activated Glomeruli in the Mouse Olfactory Bulb