Publications related to Optical Imaging Using Binary Sensors

Related publications (30)

A Statistical Framework to Investigate the Optimality of Signal-Reconstruction Methods

Michaël Unser, Pakshal Narendra Bohra, Pol del Aguila Pla

We present a statistical framework to benchmark the performance of reconstruction algorithms for linear inverse problems, in particular, neural-network-based methods that require large quantities of training data. We generate synthetic signals as realizati ...

2023

Advanced Techniques in Optical Diffraction Tomography

Ahmed Bassam Sayed Ayoub Mohamed Emam

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

Uncertain Sampling with Certain Priors

Golnooshsadat Elhami

Sampling has always been at the heart of signal processing providing a bridge between the analogue world and discrete representations of it, as our ability to process data in continuous space is quite limited. Furthermore, sampling plays a key part in unde ...

EPFL2021

Structured light engineering using a photonic nanojet

Toralf Scharf, Maryam Yousefi

In this Letter, we present the photonic nanojet as a phenomenon in a structured light generator system that is implemented to modify the source focal spot size and emission angle. The optical system comprises a microlens array that is illuminated by a focu ...

OPTICAL SOC AMER2021

Compressed sensing with signal averaging for improved sensitivity and motion artifact reduction in fluorine-19 MRI

Tobias Kober, Tom Hilbert, Ruud van Heeswijk, Jérôme Yerly

Fluorine-19 (F-19) MRI of injected perfluorocarbon emulsions (PFCs) allows for the non-invasive quantification of inflammation and cell tracking, but suffers from a low signal-to-noise ratio and extended scan time. To address this limitation, we tested the ...

WILEY2020

Three-dimensional tomography of red blood cells using deep learning

Demetri Psaltis, Joowon Lim

We accurately reconstruct three-dimensional (3-D) refractive index (RI) distributions from highly ill-posed two-dimensional (2-D) measurements using a deep neural network (DNN). Strong distortions are introduced on reconstructions obtained by the Wolf tran ...

2020

Image reconstruction for novel time domain near infrared optical tomography: towards clinical applications

Edoardo Charbon, Chunmin Zhang, Scott Anthony Lindner

Near infrared optical tomography (NIROT) is an emerging modality that enables imaging the oxygenation of tissue, which is a biomarker of tremendous clinical relevance. Measuring in reflectance is usually required when NIROT is applied in clinical scenarios ...

2020

Learning approaches to high-fidelity optical diffraction tomography

Joowon Lim

Optical diffraction tomography (ODT) provides us 3D refractive index (RI) distributions of transparent samples. Since RI values differ across different materials, they serve as endogenous contrasts. It, therefore, enables us to image without pre-processing ...

EPFL2020

CPGD: Cadzow Plug-and-Play Gradient Descent for Generalised FRI

Martin Vetterli, Paul Hurley, Matthieu Martin Jean-André Simeoni, Adrien Georges Jean Besson

Finite rate of innovation (FRI) is a powerful reconstruction framework enabling the recovery of sparse Dirac streams from uniform low-pass filtered samples. An extension of this framework, called generalised FRI (genFRI), has been recently proposed for han ...

2020

Scalar analytical expressions for the field dependence of Zernike polynomials in asymmetric optical systems with circular symmetric surfaces

Toralf Scharf, Alessandro Grosso

In this paper we derive scalar analytical expressions describing the full field dependence of Zernike polynomials in optical systems without symmetries. We consider the general case of optical systems constituted by arbitrarily tilted and decentered circul ...

2020

Imaging from Echoes: On Inverse Problems in Ultrasound

Adrien Georges Jean Besson

Ultrasound (US) imaging is currently living a revolution. On the one hand, ultrafast US imaging, a novel way of acquiring and producing US images, has paved the way to several advanced imaging modes, e.g. shear-wave elastography, ultrafast Doppler imaging ...

EPFL2018

Graph-based image representation learning

Renata Khasanova

Though deep learning (DL) algorithms are very powerful for image processing tasks, they generally require a lot of data to reach their full potential. Furthermore, there is no straightforward way to impose various properties, given by the prior knowledge a ...

EPFL2019

Optical projection tomography for whole organ imaging

David Nguyen

In the past twenty years, far-reaching studies of molecular and cellular processes have reached a milestone in their maturation, and the knowledge from these studies was ready to apply at higher organizational levels. At that time, rodent models were long ...

EPFL2019

Analysis of photosensor frontends for biomedical applications: a focus on noise

Paul Stanislas Gosselin

Photosensing has proven to be highly useful in biomedical research and medical care. Being able to detect and quantify the light emitted by fluorescent or bioluminescent reporters has significantly participated in the development of new cancer treatments a ...

EPFL2019

High Speed SAR ADC Architectures in 28nm FDSOI CMOS

Mustafa Kilic

The demand on high speed Analog to Digital Converters (ADCs) has increased considerably the last years. From communications circuit to high speed oscilloscopes, Giga Samples per second (GS/s) ADCs are requested. With the scaling of the CMOS technology, des ...

EPFL2019

Pulse-Stream Models In Time-Of-Flight Imaging

Jean-Philippe Thiran, Yves Wiaux, Adrien Georges Jean Besson, Dimitris Perdios

This paper considers the problem of reconstructing raw signals from random projections in the context of time-of-flight imaging with an array of sensors. It presents a new signal model, coined as multi-channel pulse-stream model, which exploits pulse-strea ...

IEEE2018

A Versatile Noise Performance Metric for Electrical Impedance Tomography Algorithms

Jean-Philippe Thiran, Fabian Braun, Martin Proença

Electrical impedance tomography (EIT) is an emerging technology for real-time monitoring of patients under mechanical ventilation. EIT has the potential to offer continuous medical monitoring while being noninvasive, radiation free, and low cost. Due to th ...

Ieee-Inst Electrical Electronics Engineers Inc2017

High-Quality Parallel-Ray x-Ray CT Back Projection Using Optimized Interpolation

Michaël Unser, Michael Thompson McCann

We propose a new, cost-efficient method for computing back projections in parallel-ray X-ray CT. Forward and back projections are the basis of almost all X-ray CT reconstruction methods, but computing these accurately is costly. In the special case of para ...

2017

A Fourier dimensionality reduction model for big data interferometric imaging

Jean-Philippe Thiran, Yves Wiaux, Rafael Eduardo Carrillo Rangel, Vijay Kartik

Data dimensionality reduction in radio interferometry can provide savings of computational resources for image reconstruction through reduced memory footprints and lighter computations per iteration, which is important for the scalability of imaging method ...

Oxford Univ Press2017

Near-field characterization of Bloch surface waves based 2D optical components

Richa Dubey

Bloch surface waves (BSWs) are surface electromagnetic modes that propagate at the interface between a multilayer substrate and a homogeneous external medium. The optical field of the surface mode is confined near the surface of the multilayer. This vertic ...

EPFL2017