Publications related to Practical considerations for in vivo MRI with higher dimensional spatial encoding

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

Aggregating Spatial and Photometric Context for Photometric Stereo

David Honzátko

Photometric stereo, a computer vision technique for estimating the 3D shape of objects through images captured under varying illumination conditions, has been a topic of research for nearly four decades. In its general formulation, photometric stereo is an ...

EPFL2024

Verification of the Fourier-enhanced 3D finite element Poisson solver of the gyrokinetic full-f code PICLS

Stephan Brunner, Laurent Villard, Alberto Bottino, Moahan Murugappan

We introduce and derive the Fourier -enhanced 3D electrostatic field solver of the gyrokinetic full -f PIC code PICLS. The solver makes use of a Fourier representation in one periodic direction of the domain to make the solving of the system easily paralle ...

Elsevier2024

Development and clinical validation of computational imaging biomarkers for neurodegenerative diseases

Veronica Lily Ravano

Neurodegenerative and neuroinflammatory disorders often involve complex pathophysiological mechanisms that are â to this date â only partially understood. A more comprehensive understanding of those microstructural processes and their characterization ...

EPFL2024

Impact of beam-coupling impedance on the Schottky spectrum of bunched beam

Tatiana Pieloni, Nicolas Frank Mounet, Christophe Emmanuel R. Lannoy

The Schottky monitors of the Large Hadron Collider (LHC) can be used for non-invasive beam diagnostics to estimate various bunch characteristics, such as tune, chromaticity, bunch profile or synchrotron frequency distribution. However, collective effects, ...

Iop Publishing Ltd2024

Inverse Problems in Pulse-Echo Ultrasound: Exploiting Coherence for Image Enhancement and Quantitative Imaging

Samuel Denys Beuret

Whereas pulse-echo ultrasound imaging relied on focused acoustic waves since its inception, the last two decades have seen the development of techniques based on unfocused waves, including ultrafast ultrasound imaging. In large part due to the emergence of ...

EPFL2024

Single-Photon Avalanche Diode Image Sensors for Harsh Radiation Environments

Ming-Lo Wu

The space industry has experienced substantial growth in recent years, leading to rapid advancements in space exploration and space-based technologies. Consequently, the study of electronics and sensor performance in extreme environments has become crucial ...

EPFL2024

Incorporating Projective Geometry into Deep Learning

Michal Jan Tyszkiewicz

In this thesis we explore the applications of projective geometry, a mathematical theory of the relation between 3D scenes and their 2D images, in modern learning-based computer vision systems. This is an interesting research question which contradicts the ...

EPFL2024

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

Nonlinear interactions of ion acoustic waves explored using fast imaging decompositions

Fast camera imaging is used to study ion acoustic waves propagating azimuthally in a magnetized plasma column. The high-speed image sequences are analyzed using proper orthogonal decomposition and 2D Fourier transform, allowing to evaluate the assets and d ...

2023

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

Detecting Anomalies and Obstacles in Road Scenes

Krzysztof Maciej Lis

We address the problem of segmenting anomalies and unusual obstacles in road scenes for the purpose of self-driving safety. The objects in question are not present in the common training sets as it is not feasible to collect and annotate examples for every ...

EPFL2023

An optimal preconditioned FFT-accelerated finite element solver for homogenization

Till Junge, Ali Falsafi, Martin Ladecký

We generalize and provide a linear algebra-based perspective on a finite element (FE) ho-mogenization scheme, pioneered by Schneider et al. (2017)[1] and Leuschner and Fritzen (2018)[2]. The efficiency of the scheme is based on a preconditioned, well-scale ...

ELSEVIER SCIENCE INC2023

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

Automated neuron tracking inside moving and deforming C. elegans using deep learning and targeted augmentation

Sahand Jamal Rahi, Kseniia Korchagina

Reading out neuronal activity from three-dimensional (3D) functional imaging requires segmenting and tracking individual neurons. This is challenging in behaving animals if the brain moves and deforms. The traditional approach is to train a convolutional n ...

Nature Portfolio2023

The Claude Debussy Solo Piano Corpus

Martin Alois Rohrmeier, Johannes Hentschel, Gabriele Cecchetti, Ludovica Schaerf, Sabrina Laneve

This dataset originates from the DCML corpus initiative and contains musicological research data. For more information, please refer to its documentation page https://dcmlab.github.io/debussy_piano Please cite this dataset as Laneve, S., Schaerf ...

Zenodo2023

The diachronic development of Debussy’s musical style: a corpus study with Discrete Fourier Transform

Martin Alois Rohrmeier, Johannes Hentschel, Gabriele Cecchetti, Ludovica Schaerf, Sabrina Laneve

Claude Debussy’s personal style is typically characterised as a departure from earlier diatonic tonality, including a greater variety of pitch-class materials organised in fragmented yet coherent compositions. Exploiting the music-theoretical interpretabil ...

2023

PROBING INTRACELLULAR ELASTICITY WITH MINIMAL-HESSIAN REGISTRATION

Michaël Unser

We propose an image-based elastography method to measure the heterogeneous stiffness inside a cell and its nucleus. It uses a widely accessible setup consisting of plate compression imaged with fluorescence microscopy. Our framework recovers a spatial map ...

IEEE2023

The JPEG AI Standard: Providing Efficient Human and Machine Visual Data Consumption

Touradj Ebrahimi

The Joint Photographic Experts Group (JPEG) AI learning-based image coding system is an ongoing joint standardization effort between International Organization for Standardization (ISO), International Electrotechnical Commission (IEC), and International Te ...

IEEE COMPUTER SOC2023

On the assessment of high-quality images: advances on the JPEG AIC-3 activity

Touradj Ebrahimi, Evgeniy Upenik, Michela Testolina

Recent advances in image compression have made it both possible and desirable for image quality to approach the visually lossless range. However, the most commonly used subjective visual quality assessment protocols, e.g. those reported in ITU-T Rec. BT.50 ...

2023