Concept

Iterative reconstruction

Publications associées (28)

Towards Trustworthy Deep Learning for Image Reconstruction

The remarkable ability of deep learning (DL) models to approximate high-dimensional functions from samples has sparked a revolution across numerous scientific and industrial domains that cannot be overemphasized. In sensitive applications, the good perform ...

EPFL2024

TSLAM: a tag-based object-centered monocular navigation system for augmented manual woodworking

Yves Weinand, Julien Gamerro, Andrea Settimi, Hong-Bin Yang

TimberSLAM (TSLAM) is an object-centered, tag-based visual self-localization and mapping (SLAM) system for monocular RGB cameras. It was specifically developed to support a robust and augmented reality pipeline for close-range, noisy, and cluttered fabrica ...

2024

Demonstration of a sparse sensor placement technique to the limited diagnostic set in a fusion power plant

Artur Perek, Lorenzo Martinelli

DEMO will have a limited diagnostic set for optimization of reactor performance, and limited diagnostic coverage due to challenging reactor conditions. This poses challenges for control, especially for detachment control which is planned to be performed wi ...

Elsevier Science Sa2024

Maximum likelihood bolometry for ASDEX upgrade experiments

Olivier Claude Martin Février, Riccardo Rossi

Bolometry is an essential diagnostic for calculating the power balances and for the understanding of different physical aspects of tokamak experiments. The reconstruction method based on the Maximum Likelihood (ML) principle, developed initially for JET, h ...

Iop Publishing Ltd2023

PET REBINNING WITH REGULARIZED DENSITY SPLINES

Michaël Unser

PET reconstruction algorithms have long relied on sinogram rebinning. However, as detectors grow smaller in a recent wave of cutting-edge scanners, individual sensors no longer accrue hundreds of photons. Instead, most detect a single photon or none at all ...

IEEE2023

Exploring Novel Modalities for Optical Diffraction Tomography

Amirhossein Saba Shirvan

In the past decade, optical diffraction tomography has gained a lot of attention for its ability to create label-free three-dimensional (3D) images of the refractive index distribution of biological samples using scattered fields measured through holograph ...

EPFL2023

3D reconstruction of curvilinear one-dimensional objects viewed in transmission electron microscopy

Gulnaz Ganeeva

To obtain a more complete understanding of material microstructure at the nanoscale and to gain profound insights into their properties, there is a growing need for more efficient and precise methods that can streamline the process of 3D imaging using a tr ...

EPFL2023

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

Correlating cryo-super resolution radial fluctuations and dual-axis cryo-scanning transmission electron tomography to bridge the light-electron resolution gap

Prabhu Prasad Swain

Visualization of organelles and their interactions with other features in the native cell remains a challenge in modern biology. We have introduced cryo-scanning transmission electron tomography (CSTET), which can ac-cess 3D volumes on the scale of 1 micro ...

Elsevier2023

Proton reconstruction with the CMS-TOTEM Precision Proton Spectrometer

Matthias Finger, Konstantin Androsov, Qian Wang, Jan Steggemann, Anna Mascellani, Yiming Li, Varun Sharma, Xin Chen, Arvind Shah, Rakesh Chawla, Matteo Galli, Jian Wang, João Miguel das Neves Duarte, Tagir Aushev, Matthias Wolf, Yi Zhang, Tian Cheng, Yixing Chen, Werner Lustermann, Andromachi Tsirou, Alexis Kalogeropoulos, Andrea Rizzi, Ioannis Papadopoulos, Paolo Ronchese, Hua Zhang, Leonardo Cristella, Siyuan Wang, Jessica Prisciandaro, Tao Huang, David Vannerom, Michele Bianco, Sebastiana Gianì, Sun Hee Kim, Davide Di Croce, Kun Shi, Wei Shi, Abhisek Datta, Jian Zhao, Federica Legger, Gabriele Grosso, Ji Hyun Kim, Donghyun Kim, Zheng Wang, Sanjeev Kumar, Wei Li, Yong Yang, Ajay Kumar, Ashish Sharma, Georgios Anagnostou, Joao Varela, Csaba Hajdu, Muhammad Ahmad, Ekaterina Kuznetsova, Ioannis Evangelou, Matthias Weber, Muhammad Shoaib, Milos Dordevic, Meng Xiao, Sourav Sen, Xiao Wang, Kai Yi, Jing Li, Rajat Gupta, Muhammad Waqas, Hui Wang, Seungkyu Ha, Maren Tabea Meinhard, Pratyush Das, Miao Hu, Anton Petrov, Xin Sun, Valérie Scheurer, Muhammad Ansar Iqbal, Lukas Layer

The Precision Proton Spectrometer (PPS) of the CMS and TOTEM experiments collected 107.7 fb 1 in proton-proton (pp) collisions at the LHC at 13 TeV(Run 2). This paper describes the key features of the PPS alignment and optics calibrations, the proton recon ...

Iop Publishing Ltd2023

Scalable angular spectrum propagation

Felix Wechsler

Coherent field propagation is an essential computational tool in optics with applications ranging from computational optics and optical design to iterative field reconstructions. An improvement in the computational speed of current propagation methods is t ...

Optica Publishing Group2023

Stability of Image-Reconstruction Algorithms

Michaël Unser, Sebastian Jonas Neumayer, Pol del Aguila Pla

Robustness and stability of image-reconstruction algorithms have recently come under scrutiny. Their importance to medical imaging cannot be overstated. We review the known results for the topical variational regularization strategies ( ℓ2 and ℓ1 regulariz ...

2023

Small-angle scattering tensor tomography algorithm for robust reconstruction of complex textures

Marianne Liebi, Manuel Guizar Sicairos

The development of small-angle scattering tensor tomography has enabled the study of anisotropic nanostructures in a volume-resolved manner. It is of great value to have reconstruction methods that can handle many different nanostructural symmetries. For s ...

Int Union Crystallography2023

Accelerated deep self-supervised ptycho-laminography for three-dimensional nanoscale imaging of integrated circuits

Manuel Guizar Sicairos, Yi Jiang

Three-dimensional inspection of nanostructures such as integrated circuits is important for security and reliability assurance. Two scanning operations are required: ptychographic to recover the complex transmissivity of the specimen, and rotation of the s ...

2023

LenslessPiCam: A Hardware and Software Platform for Lensless Computational Imaging with a Raspberry Pi

Martin Vetterli, Eric Bezzam, Sepand Kashani, Matthieu Martin Jean-André Simeoni

This toolkit has everything you need to perform imaging with a lensless camera. We make use of a low-cost implementation of DiffuserCam, namely replacing the lens with a piece of tape and using the Raspberry Pi HQ camera sensor. Similar principles and meth ...

Zenodo2023

State of the Art in Dense Monocular Non-Rigid 3D Reconstruction

Pascal Fua

3D reconstruction of deformable (or non-rigid) scenes from a set of monocular 2D image observations is a long-standing and actively researched area of computer vision and graphics. It is an ill-posed inverse problem, since-without additional prior assumpti ...

WILEY2023

Vibrational NDT with Under-sampled Data through Physics-informed Neural Networks

Olga Fink

The vibrational response of solid materials and structural components is substantially governed by their mechanical and geometrical properties. Low-frequency vibrations and modal frequencies are sensitive to global geometrical deviations, while high-freque ...

2023

The Sparsity of Cycle Spinning for Wavelet-Based Solutions of Linear Inverse Problems

Michaël Unser, Rahul Parhi

The usual explanation of the efficacy of wavelet-based methods hinges on the sparsity of many real-world objects in the wavelet domain. Yet, standard wavelet-shrinkage techniques for sparse reconstruction are not competitive in practice, one reason being t ...

IEEE Institute of Electrical and Electronics Engineers2023

Data for: "A Neural-Network-Based Convex Regularizer for Inverse Problems"

Michaël Unser, Pakshal Narendra Bohra, Alexis Marie Frederic Goujon, Sebastian Jonas Neumayer, Stanislas Ducotterd

Data for: "A Neural-Network-Based Convex Regularizer for Inverse Problems". The corresponding scripts can be accessed on GitHub (https://github.com/axgoujon/convex_ridge_regularizers). The data is organized as follows: - ct_data_sets.tar.gz: contains prepr ...

Zenodo2023

Integrated electronics for time-of-flight positron emission tomography photodetectors

Andrada Alexandra Muntean

Positron emission tomography is a nuclear imaging technique well known for its use in oncology for cancer diagnosis and staging. A PET scanner is a complex machine which comprises photodetectors placed in a ring configuration that detect gamma photons gen ...

EPFL2023