Publications by Yves Wiaux | EPFL Graph Search

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We consider the problem of reconstruction of astrophysical signals probed by radio interferometers with baselines bearing a non-negligible component in the pointing direction. The visibilities measured essentially identify with a noisy and incomplete Fouri ...

Respiratory motion is a major challenge in cardiac magnetic resonance imaging (MRI) and contemporary state-of-the-art motion compensation strategies like diaphragmatic navigators still suffer from sub-optimal time efficiency. In response, k-space- based on ...

A sampling theorem on the sphere has been developed recently, requiring half as many samples as alternative equiangular sampling theorems on the sphere. A reduction by a factor of two in the number of samples required to represent a band-limited signal on ...

Incorporating wide-field considerations in interferometric imaging is of increasing importance for next-generation radio telescopes. Compressed sensing techniques for interferometric imaging have been extended to wide fields recently, recovering images in ...

Conventional ultrasound (US) image reconstruction methods rely on delay-and-sum (DAS) beamforming, which is a relatively poor solution of the image reconstruction problem. An alternative to DAS consists in using iterative techniques which require both an a ...

A new sampling theorem on the sphere has been developed recently, reducing the number of samples required to represent a band-limited signal by a factor of two for equiangular sampling schemes. For signals sparse in a spatially localised measure, such as i ...

In ultrasound (US) imaging, beamforming is usually separated from the deconvolution or some other post-processing techniques. The former processes raw data to build radio-frequency (RF) images while the latter restore high-resolution images, denoted as tis ...

Image recovery in optical interferometry is an ill-posed nonlinear inverse problem arising from incomplete power spectrum and bispectrum measurements. We review our previous work, which reformulates this nonlinear problem in the framework of tensor recover ...

In recent works, compressed sensing (CS) and convex opti- mization techniques have been applied to radio-interferometric imaging showing the potential to outperform state-of-the-art imaging algorithms in the field. We review our latest contributions [1, 2, ...

This paper reviews the application of a novel methodology for analysing the isotropy of the universe by probing the alignment of local structures in the CMB. The strength of the proposed methodology relies on the steerable wavelet filtering of the CMB sign ...

We consider images probed through incomplete and noisy Fourier coverages, both in the context of radio interferometry (RI) and of magnetic resonance imaging (MRI). We show that the quality of signal reconstruction can be signiﬁcantly enhanced by the introd ...

For the next generation of radio interferometric telescopes it is of paramount importance to incorporate wide field-of-view (WFOV) considerations in interferometric imaging, otherwise the fidelity of reconstructed images will suffer greatly. We extend comp ...

An algorithm is proposed for denoising the signal induced by cosmic strings in the cosmic microwave background (CMB). A Bayesian approach is taken, based on modeling the string signal in the wavelet domain with generalized Gaussian distributions. Good perf ...

Image recovery in optical interferometry is an ill-posed nonlinear inverse problem arising from incomplete power spectrum and bi-spectrum measurements. We formulate a linear version of the problem for the order-3 tensor formed by the tensor product of the ...

This paper considers the problem of reconstructing raw signals from random projections in the context of time-of-flight imaging with an array of sensors. It presents a new signal model, coined as multi-channel pulse-stream model, which exploits pulse-strea ...

We develop a novel sampling theorem on the sphere and corresponding fast algorithms by associating the sphere with the torus through a periodic extension. The fundamental property of any sampling theorem is the number of samples required to represent a ban ...

We discuss a novel sparsity prior for compressive imaging in the context of the theory of compressed sensing with coherent redundant dictionaries, based on the observation that natural images exhibit strong average sparsity over multiple coherent frames. W ...

We consider the problem of multiple correlated sparse signals reconstruction and propose a new implementation of structured sparsity through a reweighting scheme. We present a particular application for diffusion Magnetic Resonance Imaging data and show ho ...

The main challenge for cardiac MRI is motion. To account for respiratory motion, k-space-based self- navigation approaches have recently been introduced [1]. We took self-navigation to the next level by exploiting an image-based beat-to-beat respiratory mo ...

We consider the probe of astrophysical signals through radio interferometers with small field of view and baselines with non-negligible and constant component in the pointing direction. In this context, the visibilities measured essentially identify with a ...

Yves Wiaux

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Compressed sensing for radio interferometry: spread spectrum imaging techniques

About the performance of multi-dimensional radial self-navigation incorporating compressed sensing for free-breathing coronary MRI

Implications for compressed sensing of a new sampling theorem on the sphere

Intrinsic advantages of the w component and spherical imaging for wide-field radio interferometry

Ultrafast ultrasound imaging as an inverse problem: Matrix-free sparse image reconstruction

Sparse image reconstruction on the sphere: implications of a new sampling theorem

Beamforming-deconvolution: A novel concept of deconvolution for ultrasound imaging

Sparsity in tensor optimization for optical-interferometric imaging

PURIFY: A new algorithmic framework for next-generation radio-interferometric imaging

Steerable wavelet analysis of CMB structures alignment

Spread spectrum for interferometric and magnetic resonance imaging

Compressed sensing for wide-field radio interferometric imaging

Wavelet domain Bayesian denoising of string signal in the cosmic microwave background

A convex optimization approach for image recovery from nonlinear measurements in optical interferometry

Pulse-Stream Models In Time-Of-Flight Imaging

A novel sampling theorem on the sphere

Sparsity Averaging for Compressive Imaging

Structured sparsity through reweighting and application to diffusion MRI

Multi-dimensional radial self-navigation with non-linear reconstruction for free-breathing coronary MRI

Spread spectrum for imaging techniques in radio interferometry