Publications by Laurène Donati

A Practical Guide to Supervised Deep Learning for Bioimage Analysis: Challenges and good practices

Daniel Sage, Virginie Sophie Uhlmann, Laurène Donati

The variety of bioimage data and their quality have dramatically increased over the last decade. In parallel, the number of proposed deep learning (DL) models for their analysis grows by the day. Yet, the adequate reuse of published tools by practitioners ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

CryoGAN: A New Reconstruction Paradigm for Single-Particle Cryo-EM Via Deep Adversarial Learning

Michaël Unser, Laurène Donati, Harshit Gupta, Michael Thompson McCann

We present CryoGAN, a new paradigm for single-particle cryo-electron microscopy (cryo-EM) reconstruction based on unsupervised deep adversarial learning. In single-particle cryo-EM, the structure of a biomolecule needs to be reconstructed from a large set ...

2021

DeepImageJ: A user-friendly environment to run deep learning models in ImageJ

Michaël Unser, Daniel Sage, Laurène Donati

DeepImageJ offers a user-friendly solution in ImageJ to run trained deep learning models for biomedical image analysis. It includes guiding tools for reliable analyses, contributing to the democratization of deep learning in microscopy. ...

NATURE PORTFOLIO2021

User-Friendly Building of Reconstruction Algorithms with GlobalBioIm

Michaël Unser, Laurène Donati, Emmanuel Emilien Louis Soubies

2020

User-Friendly Building of Reconstruction Algorithms for Solving Inverse Problems

Michaël Unser, Laurène Donati, Thanh-An Michel Pham, Emmanuel Emilien Louis Soubies

IEEE2020

Joint Angular Refinement and Reconstruction for Single-Particle Cryo-EM

Michaël Unser, Laurène Donati, Mona Zehni, Emmanuel Emilien Louis Soubies

Single-particle cryo-electron microscopy (cryo-EM) reconstructs the three-dimensional (3D) structure of bio-molecules from a large set of 2D projection images with random and unknown orientations. A crucial step in the single-particle cryo-EM pipeline is 3 ...

2020

Reconstruction Methods for Cryo-Electron Microscopy: From Model-based to Data-driven

Laurène Donati

The topic of this thesis is the development of new reconstruction methods for cryo-electron microscopy (cryo-EM). Cryo-EM has revolutionized the field of structural biology over the last decade and now permits the regular discovery of biostructures. Yet, t ...

EPFL2020

Pocket guide to solve inverse problems with GlobalBioIm

Michaël Unser, Daniel Sage, Laurène Donati, Thanh-An Michel Pham, Ferréol Arnaud Marie Soulez, Michael Thompson McCann, Emmanuel Emilien Louis Soubies, Thomas Jean Debarre

GlobalBioIm is an open-source MATLAB (R) library for solving inverse problems. The library capitalizes on the strong commonalities between forward models to standardize the resolution of a wide range of imaging inverse problems. Endowed with an operator-al ...

2019

Inner-Loop-Free ADMM for Cryo-EM

Michaël Unser, Laurène Donati, Emmanuel Emilien Louis Soubies

Thanks to recent advances in signal processing, the interest for fast ℓ1-regularized reconstruction algorithms in cryo-electron microscopy (cryo-EM) has intensified. The approaches based on the alternating-direction of multipliers method (ADMM) are particu ...

IEEE2019

Fast multiscale reconstruction for Cryo-EM

Michaël Unser, Masih Nilchian, Laurène Donati

We present a multiscale reconstruction framework for single-particle analysis (SPA). The representation of three-dimensional (3D) objects with scaled basis functions permits the reconstruction of volumes at any desired scale in the real-space. This multisc ...

Elsevier2018

GlobalBioIm: A Unifying Computational Framework for Solving Inverse Problems

Michaël Unser, Laurène Donati, Ferréol Arnaud Marie Soulez, Michael Thompson McCann, Emmanuel Emilien Louis Soubies

We present a unifying framework for the development of state-of-the-art reconstruction algorithms in computational optics with a clear separation between the physical (forward model) and signal-related (regularization, incorporation of prior constraints) a ...

OSA2017

DeconvolutionLab2: An Open-Source Software for Deconvolution Microscopy

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

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

Compressed sensing for STEM tomography

Michaël Unser, Masih Nilchian, Laurène Donati

A central challenge in scanning transmission electron microscopy (STEM) is to reduce the electron radiation dosage required for accurate imaging of 3D biological nano-structures. Methods that permit tomographic reconstruction from a reduced number of STEM ...

2017

Compressed Sensing for Dose Reduction in STEM Tomography

Michaël Unser, Masih Nilchian, Laurène Donati

We designed a complete acquisition-reconstruction framework to reduce the radiation dosage in 3D scanning transmission electron microscopy (STEM). Projection measurements are acquired by randomly scanning a subset of pixels at every tilt-view (i.e., random ...

IEEE2017