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Dynamic distortion correction for functional MRI using FID navigators

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Towards a multiscale point cloud structural similarity metric

Touradj Ebrahimi, Davi Nachtigall Lazzarotto

Point clouds are effective data structures for the rep- resentation of three-dimensional media and hence adopted in a wide range of practical applications. In many cases, the portrayed data is expected to be visualized by humans. After acquisition, point c ...

IEEE2023

Tumescense monitoring system for diagnosing erectile dysfunction and methods of use

Nikolaos Stergiopoulos, Rodrigo Araujo Fraga Da Silva

Systems and methods for monitoring penile tumescence are provided that overcome the drawbacks of previously known systems by providing a wearable formed of a flexible and elastic tube having a plurality of sensors disposed on or embedded within it, the wea ...

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

Brain dynamics uncovered using a machine-learning algorithm

Mackenzie Mathis

CEBRA is a machine-learning method that can be used to compress time series in a way that reveals otherwise hidden structures in the variability of the data. It excels at processing behavioural and neural data recorded simultaneously, and it can decode act ...

NATURE PORTFOLIO2023

Data-driven modeling of beam loss in the LHC

Tatiana Pieloni, Michael Schenk, Ekaterina Krymova, Loïc Thomas Davies Coyle

In the Large Hadron Collider, the beam losses are continuously measured for machine protection. By design, most of the particle losses occur in the collimation system, where the particles with high oscilla-tion amplitudes or large momentum error are scrape ...

FRONTIERS MEDIA SA2023

Variability and reproducibility of multi-echo T2 relaxometry: Insights from multi-site, multi-session and multi-subject MRI acquisitions

Jean-Philippe Thiran, Friedhelm Christoph Hummel, Tobias Kober, Tom Hilbert, Erick Jorge Canales Rodriguez, Gabriel Girard, Elda Fischi Gomez, Gian Franco Piredda, Thomas Yu, Takuya Morishita

Quantitative magnetic resonance imaging (qMRI) can increase the specificity and sensitivity of conventional weighted MRI to underlying pathology by comparing meaningful physical or chemical parameters, measured in physical units, with normative values acqu ...

2022

3-Dimensional Fluid and White Matter Suppression Magnetic Resonance Imaging Sequence Accelerated With Compressed Sensing Improves Multiple Sclerosis Cervical Spinal Cord Lesion Detection Compared With Standard 2-Dimensional Imaging

Tobias Kober

Objectives Fluid and white matter suppression (FLAWS) is a recently proposed magnetic resonance sequence derived from magnetization-prepared 2 rapid acquisition gradient-echo providing 2 coregistered datasets with white matter- and cerebrospinal fluid-supp ...

LIPPINCOTT WILLIAMS & WILKINS2022

An optimized protocol for assessing changes in mouse whole-brain activity using opto-fMRI

Valerio Zerbi, Christina Maria Grimm

Functional magnetic resonance imaging (fMRI) in mouse brain, paired with spatially and temporally defined manipulations, offers a powerful tool to causally explain the effect of specific neuronal activity on brain network dynamics. Here, we present an opti ...

ELSEVIER2022

Diamond-Based Nanoscale Quantum Relaxometry for Sensing Free Radical Production in Cells

Mayeul Sylvain Chipaux, Hoda Shirzad

Diamond magnetometry makes use of fluorescent defects in diamonds to convert magnetic resonance signals into fluorescence. Because optical photons can be detected much more sensitively, this technique currently holds several sensitivity world records for r ...

WILEY-V C H VERLAG GMBH2022

Combining Model Driven and Data Driven Approaches for Inverse Problems in Parameter Estimation and Image Reconstruction: From Modelling to Validation

Thomas Yu

Machine learning has become the state of the art for the solution of the diverse inverse problems arising from computer vision and medical imaging, e.g. denoising, super-resolution, de-blurring, reconstruction from scanner data, quantitative magnetic reson ...

EPFL2022

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