Publications de Cédric René Jean Vonesch

DeconvolutionLab2: An Open-Source Software for Deconvolution Microscopy

Michaël Unser, Daniel Sage, Cédric René Jean Vonesch, Laurène Donati, Ferréol Arnaud Marie Soulez, Denis Fortun, Guillaume Schmit

Images in fluorescence microscopy are inherently blurred due to the limit of diffraction of light. The purpose of deconvolution microscopy is to compensate numerically for this degradation. Deconvolution is widely used to restore fine details of 3D biologi ...

2017

Optical Tomographic Image Reconstruction Based on Beam Propagation and Sparse Regularization

Michaël Unser, Cédric René Jean Vonesch, Demetri Psaltis, Ulugbek Kamilov

Optical tomographic imaging requires an accurate forward model as well as regularization to mitigate missing-data artifacts and to suppress noise. Nonlinear forward models can provide more accurate interpretation of the measured data than their linear coun ...

2016

Learning from Examples in Optical Imaging

Michaël Unser, Cédric René Jean Vonesch, Demetri Psaltis, Ulugbek Kamilov

Imaging systems can be designed using examples and methods similar to the techniques used in deep learning. We describe experimental results demonstrating optical tomography based on the learning approach. ...

OSA2016

Design of Steerable Wavelets to Detect Multifold Junctions

Michaël Unser, Cédric René Jean Vonesch, Zsuzsanna Püspöki, Virginie Sophie Uhlmann

We propose a framework for the detection of junctions in images. Although the detection of edges and key points is a well examined and described area, the multiscale detection of junction centers, especially for odd orders, poses a challenge in pattern ana ...

IEEE2015

Learning Approach to Optical Tomography

Michaël Unser, Cédric René Jean Vonesch, Demetri Psaltis, Ulugbek Kamilov, Alexandre Goy

Optical tomography has been widely investigated for biomedical imaging applications. In recent years optical tomography has been combined with digital holography and has been employed to produce high-quality images of phase objects such as cells. In this p ...

Optical Soc Amer2015

Optimized Kaiser-Bessel Window Functions for Computed Tomography

Michaël Unser, Cédric René Jean Vonesch, John Paul Ward, Masih Nilchian

Kaiser-Bessel window functions are frequently used to discretize tomographic problems because they have two desirable properties: 1) their short support leads to a low computational cost and 2) their rotational symmetry makes their imaging transform indepe ...

Ieee-Inst Electrical Electronics Engineers Inc2015

Steerable PCA for Rotation-Invariant Image Recognition

Michaël Unser, Cédric René Jean Vonesch, Frédéric Stauber

In this paper, we propose a continuous-domain version of principal-component analysis, with the constraint that the underlying family of templates appears at arbitrary orientations. We show that the corresponding principal components are steerable. Our met ...

SIAM2015

FALCON: fast and unbiased reconstruction of high-density super-resolution microscopy data

Michaël Unser, Suliana Manley, Cédric René Jean Vonesch, Hagay Kirshner, Seamus John Holden, Lina Carlini

Super resolution microscopy such as STORM and (F) PALM is now a well known method for biological studies at the nanometer scale. However, conventional imaging schemes based on sparse activation of photo-switchable fluorescent probes have inherently slow te ...

Nature Publishing Group2014

Design Of Steerable Filters For The Detection Of Micro-Particles

Michaël Unser, Cédric René Jean Vonesch, Frédéric Stauber

This paper presents two contributions. We first introduce a continuous-domain version of Principal-Component Analysis (PCA) for designing steerable filters so that they best approximate a given set of image templates. We exploit the fact that steerability ...

IEEE2013

Constrained regularized reconstruction of X-ray-DPCI tomograms with weighted-norm

Michaël Unser, Cédric René Jean Vonesch, Peter Modregger, Masih Nilchian, Stamatios Lefkimmiatis, Marco Stampanoni

In this paper we introduce a new reconstruction algorithm for X-ray differential phase-contrast Imaging (DPCI). Our approach is based on 1) a variational formulation with a weighted data term and 2) a variable-splitting scheme that allows for fast converge ...

Optical Society of America2013