Publications de Thanh-An Michel Pham

Phase Retrieval: From Computational Imaging to Machine Learning: A tutorial

Michaël Unser, Thanh-An Michel Pham, Jonathan Yuelin Dong

Phase retrieval consists in the recovery of a complex-valued signal from intensity-only measurements. As it pervades a broad variety of applications, many researchers have striven to develop phase-retrieval algorithms. Classical approaches involve techniqu ...

2023

Bayesian Inversion for Nonlinear Imaging Models Using Deep Generative Priors

Michaël Unser, Thanh-An Michel Pham, Pakshal Narendra Bohra, Jonathan Yuelin Dong

Most modern imaging systems incorporate a computational pipeline to infer the image of interest from acquired measurements. The Bayesian approach to solve such ill-posed inverse problems involves the characterization of the posterior distribution of the im ...

2022

Nonlinear Inverse Problems in Quantitative Phase Imaging

Thanh-An Michel Pham

The topic of this thesis is the development of new algorithmic reconstruction methods for quantitative phase imaging (QPI). In the past decade, advanced QPI has emerged as a valuable tool to study label-free biological samples and uncover their 3D structur ...

EPFL2022

Mechanical artifacts in optical projection tomography: classification and automatic calibration

Michaël Unser, Thanh-An Michel Pham, Jonathan Yuelin Dong, François Thierry M Marelli

Optical projection tomography (OPT) is a powerful tool for biomedical studies. It achieves 3D visualization of mesoscopic biological samples with high spatial resolution using conventional tomographic-reconstruction algorithms. However, various artifacts d ...

Optica Publishing Group2022

Diffraction Tomography from Single-Molecule Localization Microscopy: Numerical Feasibility

Michaël Unser, Thanh-An Michel Pham, Emmanuel Emilien Louis Soubies, Ferréol Arnaud Marie Soulez

Single-molecule localization microscopy (SMLM) is a fluorescence microscopy technique that achieves super-resolution imaging by sequentially activating and localizing random sparse subsets of fluorophores. Each activated fluorophore emits light that then s ...

IEEE2021

Optical diffraction tomography from single-molecule localization microscopy

Michaël Unser, Thanh-An Michel Pham, Emmanuel Emilien Louis Soubies, Ferréol Arnaud Marie Soulez

Single-molecule localization microscopy (SMLM) is a powerful method for the imaging of cellular structures. This modality delivers nanoscale resolution by sequentially activating a subset of fluorescent molecules and by extracting their super-resolved posi ...

2021

Robust Phase Unwrapping via Deep Image Prior for Quantitative Phase Imaging

Michaël Unser, Matthias Lütolf, Nathalie Brandenberg, Thanh-An Michel Pham, Fangshu Yang

Quantitative phase imaging (QPI) is an emerging label-free technique that produces images containing morphological and dynamical information without contrast agents. Unfortunately, the phase is wrapped in most imaging system. Phase unwrapping is the comput ...

2021

Optimal-Transport-Based Metric for SMLM

Michaël Unser, Daniel Sage, Thanh-An Michel Pham, Quentin Alain Denoyelle, Pol del Aguila Pla

We propose the use of Flat Metric to assess the performance of reconstruction methods for single-molecule localization microscopy (SMLM) in scenarios where the ground-truth is available. Flat Metric is intimately related to the concept of optimal transport ...

IEEE2021

User-Friendly Building of Reconstruction Algorithms for Solving Inverse Problems

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

IEEE2020

Adaptive Regularization For Three-Dimensional Optical Diffraction Tomography

Michaël Unser, Demetri Psaltis, Thanh-An Michel Pham, Emmanuel Emilien Louis Soubies, Ahmed Ayoub, Ahmed Bassam Sayed Ayoub Mohamed Emam

Optical diffraction tomography (ODT) allows one to quantitatively measure the distribution of the refractive index of the sample. It relies on the resolution of an inverse scattering problem. Due to the limited range of views as well as optical aberrations ...

IEEE2020