Publications associées à Sparse inverse problems for Fourier imaging : applications to Optical Interferometry and Diffusion Magnetic Resonance Imaging

Publications associées (40)

Simulation-based Microstructure Imaging: Towards Realistic White Matter Modeling using Monte Carlo Methods in DW-MRI

Over the last two decades, Diffusion-Weighted Magnetic Resonance Imaging (DW-MRI) has been developed as a powerful MR imaging modality that allows estimating non-invasively the microscopic structure of biological tissues by exploiting the natural motion of ...

EPFL2025

Verification of the Fourier-enhanced 3D finite element Poisson solver of the gyrokinetic full-f code PICLS

Laurent Villard, Stephan Brunner, Alberto Bottino, Moahan Murugappan

We introduce and derive the Fourier -enhanced 3D electrostatic field solver of the gyrokinetic full -f PIC code PICLS. The solver makes use of a Fourier representation in one periodic direction of the domain to make the solving of the system easily paralle ...

Elsevier2024

Impact of beam-coupling impedance on the Schottky spectrum of bunched beam

Tatiana Pieloni, Nicolas Frank Mounet, Christophe Emmanuel R. Lannoy

The Schottky monitors of the Large Hadron Collider (LHC) can be used for non-invasive beam diagnostics to estimate various bunch characteristics, such as tune, chromaticity, bunch profile or synchrotron frequency distribution. However, collective effects, ...

Iop Publishing Ltd2024

Tangentially viewing phase contrast imaging for turbulence measurements in toroidal fusion devices

Stefano Coda

Phase contrast imaging (PCI) is an established and powerful technique for measuring density fluctuations in plasmas and has been successfully applied to several fusion devices. Rooted in a concept first developed for microscopy, PCI belongs to the category ...

2024

Towards Trustworthy Deep Learning for Image Reconstruction

Alexis Marie Frederic Goujon

The remarkable ability of deep learning (DL) models to approximate high-dimensional functions from samples has sparked a revolution across numerous scientific and industrial domains that cannot be overemphasized. In sensitive applications, the good perform ...

EPFL2024

Statistical Inference for Inverse Problems: From Sparsity-Based Methods to Neural Networks

Pakshal Narendra Bohra

In inverse problems, the task is to reconstruct an unknown signal from its possibly noise-corrupted measurements. Penalized-likelihood-based estimation and Bayesian estimation are two powerful statistical paradigms for the resolution of such problems. They ...

EPFL2024

Unified Harmonic Power-Flow and Stability Analysis of Power Grids with Converter-Interfaced Distributed Energy Resources

Johanna Kristin Maria Becker

Modern power distribution systems are experiencing a large-scale integration of Converter-Interfaced Distributed Energy Resources (CIDERs). Their presence complicates the analysis and mitigation of harmonics, whose creation and propagation may be amplified ...

EPFL2024

Learning the intrinsic dynamics of spatio-temporal processes through Latent Dynamics Networks

Alfio Quarteroni, Francesco Regazzoni, Stefano Pagani

Predicting the evolution of systems with spatio-temporal dynamics in response to external stimuli is essential for scientific progress. Traditional equations-based approaches leverage first principles through the numerical approximation of differential equ ...

Nature Portfolio2024

Stability of the Faber-Krahn inequality for the short-time Fourier transform

Jaime Gómez Ramírez, Joao Pedro Gonçalves Ramos

We prove a sharp quantitative version of the Faber–Krahn inequality for the short-time Fourier transform (STFT). To do so, we consider a deficit which measures by how much the STFT of a function fails to be optimally concentrated on an arbitrary set of pos ...

Springer Heidelberg2024

Subwavelength imaging using a solid-immersion diffractive optical processor

Demetri Psaltis, Niyazi Ulas Dinç, Carlo Gigli

Phase imaging is widely used in biomedical imaging, sensing, and material characterization, among other fields. However, direct imaging of phase objects with subwavelength resolution remains a challenge. Here, we demonstrate subwavelength imaging of phase ...

Springernature2024

SPACE-TIME REDUCED BASIS METHODS FOR PARAMETRIZED UNSTEADY STOKES EQUATIONS

Simone Deparis, Riccardo Tenderini

In this work, we analyze space-time reduced basis methods for the efficient numerical simulation of haemodynamics in arteries. The classical formulation of the reduced basis (RB) method features dimensionality reduction in space, while finite difference sc ...

Siam Publications2024

A Continuous-Domain Solution for Computed Tomography with Hessian Total-Variation Regularization

Youssef Haouchat, Michaël Unser, Mehrsa Pourya

We formulate computed-tomography reconstruction as a continuous-domain optimization problem with Hessian total variation (HTV) as the regularizer. HTV is a sparsity-promoting regularizer that favors continuous and piecewise-linear functions with few affine ...

IEEE Computer Society2024

Adding Color to Mass Spectra of Biopolymers: Charge Determination Analysis (CHARDA) Assigns Charge State to Every Ion Peak

Yury Tsybin, Natalia Gasilova, Laure Menin, Anton Kozhinov, Konstantin Nagornov

Traditionally, mass spectrometry (MS) output is the ion abundance plotted versus the ionic mass-to-charge ratio m/z. While employing only commercially available equipment, Charge Determination Analysis (CHARDA) adds a third dimension to MS, estimating for ...

Amer Chemical Soc2024

Fourier analysis of near-field patterns generated by propagating polaritons

Giulia Tagliabue

Scattering-type scanning near-field optical microscope (s-SNOM) has become an essential tool to study polaritons—quasiparticles of light coupled to collective charge oscillations—via direct probing of their near field with a spatial resolution far beyond t ...

American Physical Society (APS)2024

Discrete choice modeling in the era of big data

Nicola Marco Ortelli

The technological advancements of the past decades have allowed transforming an increasing part of our daily actions and decisions into storable data, leading to a radical change in the scale and scope of available data in relation to virtually any object ...

EPFL2024

The diachronic development of Debussy’s musical style: a corpus study with Discrete Fourier Transform

Martin Alois Rohrmeier, Johannes Hentschel, Gabriele Cecchetti

Claude Debussy’s personal style is typically characterised as a departure from earlier diatonic tonality, including a greater variety of pitch-class materials organised in fragmented yet coherent compositions. Exploiting the music-theoretical interpretabil ...

2023

Multi-Frequency Tracking via Group-Sparse Optimal Transport

Isabel Haasler

In this letter, we introduce an optimal transport framework for inferring power distributions over both spatial location and temporal frequency. Recently, it has been shown that optimal transport is a powerful tool for estimating spatial spectra that chang ...

Ieee-Inst Electrical Electronics Engineers Inc2024

Learning a Convex Patch-Based Synthesis Model via Deep Equilibrium

Michaël Unser, Sebastian Jonas Neumayer, Stanislas Ducotterd

We investigate the learning of a convex patch-based synthesis model for the reconstruction of images. In essence, we propose to learn a dictionary via bilevel optimization for denoising. Using implicit differentiation, we find a closed-form formula of the ...

IEEE2024

Computation of the attenuation function of the lightning return-stroke current from electromagnetic fields measured in a short-duration time-window, Part I: Theoretical investigation

Farhad Rachidi-Haeri, Marcos Rubinstein

In a recent paper, a procedure to reconstruct the attenuation function of a return-stroke current from the simultaneous measurements of the channel-base current and the radiated electromagnetic fields was presented. One of the assumptions of the whole fram ...

Elsevier2023

Exploring the effectiveness of using internal CNC system signals for chatter detection in milling process

Dimitrios Kyritsis, Xiaochen Zheng

Chatter is a harmful self-excited vibration that commonly occurs during milling processes. Data -driven chatter detection and prediction is critical to achieve high surface quality and process efficiency. Most existing chatter detection approaches are base ...

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD2023