Publications related to Practical considerations of diffusion-weighted MRS with ultra-strong diffusion gradients

Related publications (31)

Streamline RimNet: Tools for Automatic Classification of Paramagnetic Rim Lesions in MRI of Multiple Sclerosis

Joe Najm, Meritxell Bach Cuadra, Cristina Granziera, Francesco La Rosa

This site provides two software tools related to "RimNet: A deep 3D multimodal MRI architecture for paramagnetic rim lesion assessment in multiple sclerosis" by Barquero et al. NeuroImage: Clinical (2020). People using in part or f ...

Zenodo2023

A robust walking detection algorithm using a single foot-worn inertial sensor: validation in real-life settings

Kamiar Aminian, Anisoara Ionescu, Gaëlle Prigent

Walking activity and gait parameters are considered among the most relevant mobility-related parameters. Currently, gait assessments have been mainly analyzed in laboratory or hospital settings, which only partially reflect usual performance (i.e., real wo ...

SPRINGER HEIDELBERG2023

Axial and radial axonal diffusivities and radii from single encoding strongly diffusion-weighted MRI

Erick Jorge Canales Rodriguez, Marco Pizzolato

We enable the estimation of the per-axon axial diffusivity from single encoding, strongly diffusion-weighted, pulsed gradient spin echo data. Additionally, we improve the estimation of the per-axon radial diffusivity compared to estimates based on spherica ...

ELSEVIER2023

E-Scan: Consuming Contextual Data with Model Plugins

Anastasia Ailamaki, Viktor Sanca

Extracting value and insights from increasingly heterogeneous data sources involves multiple systems combining and consuming the data. With multi-modal and context-rich data such as strings, text, videos, or images, the problem of standardizing the data mo ...

2023

New insights into rodent brain microstructure and metabolism in hepatic encephalopathy

Jessie Julie Mosso

Type C hepatic encephalopathy (HE) is a severe neuropsychiatric complication of chronic liver disease, for which the prognosis is poor in the absence of liver transplantation. Cirrhosis in type C HE leads to a toxic accumulation of ammonia in the blood, wh ...

EPFL2023

Reinforcement Learning for Joint Design and Control of Battery-PV Systems

Christophe Ballif, Nicolas Würsch, Laure-Emmanuelle Perret Aebi, Marine Dominique Cauz

The decentralisation and unpredictability of new renewable energy sources require rethinking our energy system. Data-driven approaches, such as reinforcement learning (RL), have emerged as new control strategies for operating these systems, but they have n ...

2023

Optimizing Data Processing for Nanodiamond Based Relaxometry

Mayeul Sylvain Chipaux

The nitrogen-vacancy (NV) center in diamond is a powerful and versatile quantum sensor for diverse quantities. In particular, relaxometry (or T1), can be used to detect magnetic noise at the nanoscale. For experiments with single NV centers the analysis of ...

WILEY2023

Dielectric metasurfaces and their applications for optical biosensing

Yasaman Jahani

Over the past century, our understanding of life has been focused on its most fundamental building blocks: molecules. Biological molecules, such as proteins found in blood, other body fluids, or tissues, are excellent guides to identifying a normal or abno ...

EPFL2023

An Error-Based Approximation Sensing Circuit for Event-Triggered Low-Power Wearable Sensors

David Atienza Alonso, Alexandre Sébastien Julien Levisse, Tomas Teijeiro Campo, Flavio Ponzina, Silvio Zanoli

Event-based sensors have the potential to optimize energy consumption at every stage in the signal processing pipeline, including data acquisition, transmission, processing, and storage. However, almost all state-of-the-art systems are still built upon th ...

2023

Boosting Efficiency of External Pipelines by Blurring Application Boundaries

Anastasia Ailamaki, Periklis Chrysogelos, Anna Patricia Herlihy

Modern application development addresses increasingly specialized problems using domain-specific utilities, such as Optical Code Recognition and standalone statistical tools. The diversity of tooling, combined with the ever-growing volume of data, requires ...

2022

Detecting Latent Training Needs Using Large Datasets

Ramtin Yazdanian

In today's world, there is no shortage of disruptors acting on various professional domains. The Fourth Industrial Revolution, with its AI-driven and automation-focused technologies, has fundamentally changed many domains -- particularly the Information an ...

EPFL2022

Lightweight HI source finding for next generation radio surveys

Jean-Paul Richard Kneib, Frédéric Courbin, Aymeric Alexandre Galan, Austin Chandler Peel, Emma Elizabeth Tolley, Mark Thomas Sargent

Future deep HI surveys will be essential for understanding the nature of galaxies and the content of the Universe. However, the large volume of these data will require distributed and automated processing techniques. We introduce LiSA, a set of python modu ...

ELSEVIER2022

Neurite Exchange Imaging ((NEXI): A minimal model of diffusion in gray matter with inter-compartment water exchange

Alexandre Jean François Marie De Skowronski, Ileana Ozana Jelescu

Biophysical models of diffusion in white matter have been center-stage over the past two decades and are essentially based on what is now commonly referred to as the "Standard Model" (SM) of non-exchanging anisotropic compartments with Gaussian diffusion. ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2022

BMAT: An open-source BIDS managing and analysis tool

Meritxell Bach Cuadra, Francesco La Rosa

Magnetic Resonance Imaging (MRI) is an established technique to study in vivo neurological disorders such as Multiple Sclerosis (MS). To avoid errors on MRI data organization and automated processing, a standard called Brain Imaging Data Structure (BIDS) h ...

ELSEVIER SCI LTD2022

PIRACY: An Optimized Pipeline for Functional Connectivity Analysis in the Rat Brain

Rolf Gruetter, Ileana Ozana Jelescu, Ting Yin, Yujian Diao

Resting state functional MRI (rs-fMRI) is a widespread and powerful tool for investigating functional connectivity (FC) and brain disorders. However, FC analysis can be seriously affected by random and structured noise from non-neural sources, such as phys ...

2021

Open-access quantitative MRI data of the spinal cord and reproducibility across participants, sites and manufacturers

Dimitri Nestor Alice Van De Ville, Maxime Descoteaux, Nawal Noëlle Kinany

In a companion paper by Cohen-Adad et al. we introduce the spine generic quantitative MRI protocol that provides valuable metrics for assessing spinal cord macrostructural and microstructural integrity. This protocol was used to acquire a single subject da ...

NATURE PORTFOLIO2021

Crypt4GH: a file format standard enabling native access to encrypted data

Juan Ramón Troncoso-Pastoriza

Motivation: The majority of genome analysis tools and pipelines require data to be decrypted for access. This potentially leaves sensitive genetic data exposed, either because the unencrypted data is not removed after analysis, or because the data leaves t ...

Oxford University Press2021

Integrating Inland and Coastal Water Quality Data for Actionable Knowledge

Damien Bouffard, Camille Roland Marie Minaudo, Theo Baracchini

Water quality measures for inland and coastal waters are available as discrete samples from professional and volunteer water quality monitoring programs and higher-frequency, near-continuous data from automated in situ sensors. Water quality parameters als ...

MDPI2021

Jointly Optimizing Sensing Pipelines for Multimodal Mixed Reality Interaction

Lakmal Buddika Meegahapola

Natural human interactions for Mixed Reality Applications are overwhelmingly multimodal: humans communicate intent and instructions via a combination of visual, aural and gestural cues. However, supporting low-latency and accurate comprehension of such mul ...

IEEE COMPUTER SOC2020

Apparent diffusion coefficient measured by diffusion MRI of moving and deforming domains

Jan Sickmann Hesthaven

The modeling of the diffusion MRI signal from moving and deforming organs such as the heart is challenging due to significant motion and deformation of the imaged medium during the signal acquisition. Recently, a mathematical formulation of the Bloch-Torre ...

Academic Press Inc - Elsevier Science2020