Publications associées à Data-driven myelin water imaging based on T-1 and T-2 relaxometry

Publications associées (20)

Machine learning enhanced tomographic reconstruction for multispectral imaging on TCV

A multispectral camera setup is used to infer a 2D map of plasma parameters in a tokamak from spectral emissions. However, the light measured by these cameras is line integrated in the toroidal direction, whereas emissivities on the poloidal plane are nece ...

2025

From Pose to Behavior: Advancing Multi-Individual Pose Estimation and Hierarchical Action Segmentation with Transformers

Lucas Maximilian Stoffl

Accurately measuring behavior is critical to understanding brain function. While traditional behavioral analysis has relied on human observation and manual processing, advances in machine learning and computer vision have begun to automate the field. This ...

EPFL2025

Rapid prediction of phonon density of states by crystal attention graph neural network and high-throughput screening of candidate substrates for wide bandgap electronic cooling

Changpeng Lin

Machine learning has demonstrated superior performance in predicting vast materials properties. However, predicting a spectral-like continuous material property such as phonon density of states (DOS) is more challenging for machine learning. In this work, ...

2025

Fully data-driven and modular building thermal control with physically consistent modeling

Benjamin Bejar Haro, Carl Pierre Jacques Remlinger

Machine learning has experienced significant growth in the smart building sector, whether for building modeling or energy management. Data-driven approaches leverage available measurements to bypass the slow and costly calibration of physics-based models, ...

2025

EntitySAM: Segment Everything in Video

Mingqiao Ye

Automatically tracking and segmenting every video entity remains a significant challenge. Despite rapid advancements in video segmentation, even state-of-the-art models like SAM 2 struggle to consistently track all entities across a video—a task we refer t ...

IEEE2025

Euclid preparation: LXVI. Impact of line-of-sight projections on the covariance between galaxy cluster multi-wavelength observable properties: Insights from hydrodynamic simulations

Frédéric Courbin, Georges Meylan

Context. Cluster cosmology can benefit from combining multi-wavelength studies. In turn, these studies benefit from a characterisation of the correlation coefficients among different mass-observable relations. Aims. In this work, we aim to provide informat ...

EDP Sciences2025

Explainable AI guided unsupervised fault diagnostics for high-voltage circuit breakers

Olga Fink, Gaëtan Michel Frusque, Florent Evariste Forest

Commercial high-voltage circuit breaker (CB) condition monitoring systems rely on directly observable physical parameters such as gas filling pressure with pre-defined thresholds. While these parameters are crucial, they only cover a small subset of malfun ...

2025

Predicting High-magnification Events in Microlensed Quasars in the Era of LSST Using Recurrent Neural Networks

Eric Gérard Guy Paic, Favio César Neira Diaz

Upcoming wide-field surveys, such as the Rubin Observatory's Legacy Survey of Space and Time (LSST), will monitor thousands of strongly lensed quasars over a 10 yr period. Many of these monitored quasars will undergo high-magnification events (HMEs) throug ...

IOP Publishing Ltd2025

Value of MRI-T2 Mapping to Differentiate Clinically Significant Prostate Cancer

Tom Hilbert

Standardized reporting of multiparametric prostate MRI (mpMRI) is widespread and follows international standards (Pi-RADS). However, quantitative measurements from mpMRI are not widely comparable. Although T2 mapping sequences can provide repeatable quanti ...

SPRINGER2024

NNG-Mix: Improving Semi-Supervised Anomaly Detection with Pseudo-Anomaly Generation

Olga Fink, Gaëtan Michel Frusque

Anomaly detection (AD) is essential in identifying rare and often critical events in complex systems, finding applications in fields such as network intrusion detection, financial fraud detection, and fault detection in infrastructure and industrial system ...

2024

Native learning ability and not age determines the effects of brain stimulation

Friedhelm Christoph Hummel, Traian Popa, Pablo Maceira Elvira, Andéol Geoffroy Cadic-Melchior, Anne-Christine Schmid

Healthy aging often entails a decline in cognitive and motor functions, affecting independence and quality of life in older adults. Brain stimulation shows potential to enhance these functions, but studies show variable effects. Previous studies have tried ...

2024

Structure-based drug design with equivariant diffusion models

Bruno Emanuel Ferreira De Sousa Correia, Arne Schneuing, Ilia Igashov

Structure-based drug design (SBDD) aims to design small-molecule ligands that bind with high affinity and specificity to pre-determined protein targets. Generative SBDD methods leverage structural data of drugs with their protein targets to propose new dru ...

SPRINGERNATURE2024

Prediction of mycotoxin response of DNA-wrapped nanotube sensor with machine learning

Ardemis Anoush Boghossian, Sara Behjati, Sayyed Hashem Sajjadi, Yahya Rabbani

DNA-wrapped single-walled carbon nanotubes (DNA-SWCNTs) have demonstrated great versatility as optical sensors. SWCNTs emit a near-infrared fluorescence that is responsive to the slightest changes in their environment, enabling the creation of sensors that ...

2023

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

Data analysis techniques for the visualization and classification of historical vehicle engines' health status using data-driven solutions

Alejandro Roda Buch

In the field of cultural heritage, the use of non-destructive techniques to determine the state ofconservation of an artifact is of the utmost importance, to avoid damage to the object itself. In this paper, we present a data pipeline and several machine l ...

ASSOC PROFISSIONAL CONSERVADORES-RESTAURADORES PORTUGAL2023

Hardware-Software Co-design for Improved Resource Utilization in DNN Accelerators

Ahmet Caner Yüzügüler

Deep neural networks (DNN) have become an essential tool to tackle challenging tasks in many fields of computer science. However, their high computational complexity limits their applicability. Specialized DNN accelerators have been developed to accommodat ...

EPFL2023

Dynamic nuclear polarisation of 1H in Gd-doped In(OH)3

David Lyndon Emsley, Michael Allan Hope, Amrit Venkatesh, Yuxuan Zhang

Dynamic nuclear polarisation (DNP) of solids doped with high-spin metal ions, such as Gd3+, is a useful strategy to enhance the nuclear magnetic resonance (NMR) sensitivity for these samples. Spin diffusion can relay polarisation throughout a sample, which ...

Academic Press Inc - Elsevier Science2023

How to combine the use of intraoperative magnetic resonance imaging (MRI) and awake craniotomy for microsurgical resection of hemorrhagic cavernous malformation in eloquent area: a case report

Constantin Tuleasca

BackgroundCavernous malformations are clusters of abnormal and hyalinized capillaries without interfering brain tissue. Here, we present a cavernous malformation operated under awake conditions, due to location, in an eloquent area and using intraoperative ...

2023

Hardware Implementation of Digital Signal Processing Algorithms for Programmable Epilepsy Control Systems

Keyvan Farhang Razi

Epilepsy is a common chronic neurological disorder that causes recurring seizures and affects more than 50 million people worldwide. Implantable medical devices (IMDs) are regarded as effective tools to cure patients who suffer from refractory epilepsy. Se ...

EPFL2023

Redox and Immune Signaling in Schizophrenia: New Therapeutic Potential

Lijing Xin

Redox biology and immune signaling play major roles in the body, including in brain function. A rapidly growing literature also suggests that redox and immune abnormalities are implicated in neuropsychiatric conditions such as schizophrenia (SZ), bipolar d ...

OXFORD UNIV PRESS2023