Publication

Efficient Inversion of Multiple-Scattering Model for Optical Diffraction Tomography

Publications associées (29)

Advanced Techniques in Optical Diffraction Tomography

In this thesis, we study the 3 challenges described above. First, we study different reconstruction techniques and assess the fidelity of each reconstruction results by means of structured illumination and phase conjugation. By reconstructing the 3D refrac ...

EPFL2022

Amplitude and phase reconstruction for Low-Energy Electron Holography of individual proteins

Hannah Julia Ochner

Single-molecule imaging methods are of importance in structural biology, and specifically in the imaging of proteins, since they can elucidate conformational variability and structural changes that might be lost in imaging methods relying on averaging proc ...

EPFL2022

High sensitivity, incoherent differential imaging

Chiara Bonati

Microscopic visualisation of optically transparent samples has been a topic of interest for several decades. Features such as density or chemical composition can influence the optical phase of transmitted light, and phase contrast can reveal these structur ...

EPFL2022

Phase Reconstruction of Low-Energy Electron Holograms of Individual Proteins

Klaus Kern, Stephan Rauschenbach, Sven Alexander Szilagyi, Hannah Julia Ochner

Low-energy electron holography (LEEH) is one of the few techniques capable of imaging large and complex three-dimensional molecules, such as proteins, on the single molecule level at subnanometer resolution. During the imaging process, the structural infor ...

AMER CHEMICAL SOC2022

Lock-in incoherent differential phase contrast imaging

Christophe Moser, Damien Claude-Marie Loterie, Timothé Laforest, Chiara Bonati

We introduce a lock-in method to increase the phase contrast in incoherent differential phase contrast (DPC) imaging. This method improves the phase sensitivity by the analog removal of the background. The use of a smart pixel detector with in-pixel signal ...

CHINESE LASER PRESS2022

Physics-informed neural networks for diffraction tomography

Demetri Psaltis, Ahmed Ayoub, Carlo Gigli, Amirhossein Saba Shirvan

We propose a physics-informed neural network (PINN) as the forward model for tomographic reconstructions of biological samples. We demonstrate that by training this network with the Helmholtz equation as a physical loss, we can predict the scattered field ...

SPIE-SOC PHOTO-OPTICAL INSTRUMENTATION ENGINEERS2022

Glass-in-glass infiltration for 3D micro-optical composite components

Yves Bellouard, Andreas Mortensen, Jérôme Faist, Enrico Casamenti, Luciano Borasi, Gözden Torun, Mathieu Bertrand

Chalcogenide glass exhibits a wide transmission window in the infrared range, a high refractive index, and nonlinear optical properties; however, due to its poor mechanical properties and low chemical and environmental stability, producing three-dimensiona ...

2022

Lock-in amplified differential phase contrast

Christophe Moser, Damien Claude-Marie Loterie, Timothé Laforest, Chiara Bonati

We introduce a lock-in method to increase the phase contrast in incoherent Differential Phase Contrast (DPC) imaging. The use of a smart pixel detector with in-pixel signal demodulation, paired with synchronized illumination, provides the basis of a bit-ef ...

SPIE-INT SOC OPTICAL ENGINEERING2022

Combining Model Driven and Data Driven Approaches for Inverse Problems in Parameter Estimation and Image Reconstruction: From Modelling to Validation

Thomas Yu

Machine learning has become the state of the art for the solution of the diverse inverse problems arising from computer vision and medical imaging, e.g. denoising, super-resolution, de-blurring, reconstruction from scanner data, quantitative magnetic reson ...

EPFL2022