Cédric René Jean Vonesch

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We present a multilevel extension of the popular "thresholded Landweber" algorithm for wavelet-regularized image restoration that yields an order of magnitude speed improvement over the standard fixed-scale implementation. The method is generic and targete ...

With the recent development of fluorescent probes and new high-resolution microscopes, biological imaging has entered a new era and is presently having a profound impact on the way research is being conducted in the life sciences. Biologists have come to d ...

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 ...

X-ray differential phase-contrast tomography is a recently-developed modality for the imaging of low-contrast biological samples. Its mathematical model is based on the first derivative of the Radon transform and the images, in practice, are reconstructed ...

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 ...

We propose a novel denoising algorithm to reduce the Poisson noise that is typically dominant in fluorescence microscopy data. To process large datasets at a low computational cost, we use the unnormalized Haar wavelet transform. Thanks to some of its appe ...

Interannual to multidecadal variability of winter storminess in the eastern United States was studied using water level measurements from coastal tide gauges. The proximity to the coast of the primary winter storm track in the region allows the use of tide ...

The subject of this thesis is image restoration, that is, deconvolution and denoising. Our work is motivated by applications in the rapidly expanding field of biological imaging and in particular fluorescence microscopy. Inverse problems in this area typic ...

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 ...

We propose a reconstruction scheme adapted to MRI that takes advantage of a sparsity constraint in the wavelet domain. We show that, artifacts are significantly reduced compared to conventional reconstruction methods. Our approach is also competitive with ...

We present a fast algorithm for image restoration in the presence of Poisson noise. Our approach is based on (1) the minimization of an unbiased estimate of the MSE for Poisson noise, (2) a linear parametrization of the denoising process and (3) the preser ...

We present a fast variational deconvolution algorithm that minimizes a quadratic data term subject to a regularization on the

\ell ^{ 1 }

-norm of the wavelet coefficients of the solution. Previously available methods have essentially consisted in alte ...

As the field of bioimage informatics matures, the issue of the validation of image reconstruction algorithms and the definition of proper performance criteria becomes more pressing. In this work, we discuss benchmarking aspects of fluorescence microscopy q ...

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 ...

We present a modified version of the deconvolution algorithm introduced by Figueiredo and Nowak, which leads to a substantial acceleration. The algorithm essentially consists in alternating between a Landweber-type iteration and a wavelet-domain denoising ...

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 ...

We present a method for designing steerable wavelets that can detect local centers of symmetry in images. Based on this design, we then propose an algorithm for estimating the locations and the orientations of M-fold symmetric junctions in biological micro ...

Wavelet-domain l(1)-regularization is a promising approach to deconvolution. The corresponding variational problem can be solved using a "thresholded Landweber" (TL) algorithm. While this iterative procedure is simple to implement, it is known to converge ...

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 ...

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 ...

Cédric René Jean Vonesch

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A Fast Multilevel Algorithm for Wavelet-Regularized Image Restoration

The Colored Revolution of Bioimaging

Learning Approach to Optical Tomography

Iterative FBP For Improved Reconstruction Of X-Ray Differential Phase-Contrast Tomograms

DeconvolutionLab2: An Open-Source Software for Deconvolution Microscopy

Fast Haar-Wavelet Denoising Of Multidimensional Fluorescence Microscopy Data

Variability of Winter Storminess in the Eastern United States during the Twentieth Century from Tide Gauges

Fast and automated wavelet-regularized image restoration in fluorescence microscopy

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

Wavelet-Regularized Reconstruction For Rapid MRI

Fast Interscale Wavelet Denoising of Poisson-Corrupted Images

A Fast Thresholded Landweber Algorithm for Wavelet-Regularized Multidimensional Deconvolution

Benchmarking Image-Processing Algorithms for Biomicroscopy: Reference Datasets and Perspectives

Optimized Kaiser-Bessel Window Functions for Computed Tomography

Fast wavelet regularized image deconvolution

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

Detection Of Symmetric Junctions In Biological Images Using 2-D Steerable Wavelet Transforms

A fast thresholded landweber algorithm for general wavelet bases: Application to 3D deconvolution microscopy

Design of Steerable Wavelets to Detect Multifold Junctions

Optical Tomographic Image Reconstruction Based on Beam Propagation and Sparse Regularization