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Jonas Richiardi

Cette personne a quitté l’EPFL

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Publications associées (26)

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Probabilistic models for multi-classifier biometric authentication using quality measures

Jonas Richiardi

Biometric authentication can be cast as a signal processing and statistical pattern recognition problem. As such, it relies on models of signal representations that can be used to discriminate between classes. One of the assumptions typically made by the p ...

EPFL2008

Low-level grounding in a multimodal mobile service robot conversational system using graphical models

Jonas Richiardi, Andrzej Drygajlo, Plamen Prodanov, Anil Alexander

The main task of a service robot with a voice-enabled communication interface is to engage a user in dialogue providing an access to the services it is designed for. In managing such interaction, inferring the user goal (intention) from the request for a s ...

Springer-Verlag2008

Multi-centre classification of functional neurological disorders based on resting-state functional connectivity

Dimitri Nestor Alice Van De Ville, Jonas Richiardi

Background: Patients suffering from functional neurological disorder (FND) experience disabling neurological symptoms not caused by an underlying classical neurological disease (such as stroke or multiple sclerosis). The diagnosis is made based on reliable ...

ELSEVIER SCI LTD2022

Event-related potentials and changes of brain rhythm oscillations during working memory activation in patients with first-episode psychosis

Jonas Richiardi

Background: Earlier contributions have documented significant changes in sensory, attention-related endogenous event-related potential (ERP) components and theta band oscillatory responses during working memory activation in patients with schizophrenia. In ...

2012

Connectivity Searchlight: A Novel Approach For Mri Information Mapping Using Multivariate Connectivity

Dimitri Nestor Alice Van De Ville, Jonas Richiardi

Brain mapping using magnetic resonance imaging (MRI) is traditionally performed using voxel-wise statistical hypothesis testing. Such mass-univariate approach ignores subtle spatial interactions. The searchlight method, in contrast, uses a multivariate pre ...

Ieee2013

Bayesian networks and information theory for audio-visual perception modeling

Jonas Richiardi, Patricia Besson

Thanks to their different senses, human observers acquire multiple information coming from their environment. Complex cross-modal interactions occur during this perceptual process. This article proposes a framework to analyze and model these interactions t ...

2010

Removing Facial Features From Structural Mri Images Biases Visual Quality Assessment

Patric Hagmann, Elda Fischi Gomez, Oscar Esteban Rucavado Leandro, Jonas Richiardi, Thomas Sanchez

A critical step before data-sharing of human neuroimaging is removing facial features to protect individuals' privacy. However, not only does this process redact identifiable information about individuals, but it also removes non-identifiable information. ...

PUBLIC LIBRARY SCIENCE2025

Multicontrast connectometry: A new tool to assess cerebellum alterations in early relapsing‐remitting multiple sclerosis

Jean-Philippe Thiran, Dimitri Nestor Alice Van De Ville, Alessandro Daducci, Gunnar Krüger, Djalel Eddine Meskaldji, Gloria Menegaz, Cristina Granziera, David Paul Roger Romascano, Alexis Roche, Jonas Richiardi, Ying-Chia Lin, Guillaume Bonnier

Background: Cerebellar pathology occurs in late multiple sclerosis (MS) but little is known about cerebellar changes during early disease stages. In this study, we propose a new multicontrast “connectometry” approach to assess the structural and functional ...

Wiley-Blackwell2015

Decoding brain states from fMRI connectivity graphs

Dimitri Nestor Alice Van De Ville, Jonas Richiardi

Functional connectivity analysis of fMRI data can reveal synchronised activity between anatomically distinct brain regions. Here, we extract the characteristic connectivity signatures of different brain states to perform classification, allowing us to deco ...

2011

The Multiscenario Multienvironment BioSecure Multimodal Database (BMDB)

Norman Hoon Thian Poh, Jonas Richiardi, Andrzej Drygajlo

A new multimodal biometric database designed and acquired within the framework of the European BioSecure Network of Excellence is presented. It is comprised of more than 600 individuals acquired simultaneously in three scenarios: 1) over the Internet, 2) i ...

2010

Plasma neurofilament light and phosphorylated tau 181 as biomarkers of Alzheimer's disease pathology and clinical disease progression

Bénédicte Marie Maréchal, Jonas Richiardi, Christopher Clark

BackgroundTo assess the performance of plasma neurofilament light (NfL) and phosphorylated tau 181 (p-tau181) to inform about cerebral Alzheimer's disease (AD) pathology and predict clinical progression in a memory clinic setting.MethodsPlasma NfL and p-ta ...

2021

Promoting diversity in Gaussian mixture ensembles: an application to signature verification

Jonas Richiardi, Andrzej Drygajlo

Classifiers based on Gaussian mixture models are good performers in many pattern recognition tasks. Unlike decision trees, they can be described as stable classifier: a small change in the sampling of the training set will produce not a large change in the ...

Springer2008

CVSnet: A machine learning approach for automated central vein sign assessment in multiple sclerosis

Reto Meuli, Tobias Kober, Meritxell Bach Cuadra, Cristina Granziera, Jonas Richiardi, Francesco La Rosa, João Pedro Forjaco Jorge

The central vein sign (CVS) is an efficient imaging biomarker for multiple sclerosis (MS) diagnosis, but its application in clinical routine is limited by inter-rater variability and the expenditure of time associated with manual assessment. We describe a ...

2020

Artificial Intelligence in Musculoskeletal Imaging: Review of Current Literature, Challenges, and Trends

Tobias Kober, Jonas Richiardi

Artificial intelligence (AI) has gained major attention with a rapid increase in the number of published articles, mostly recently. This review provides a general understanding of how AI can or will be useful to the musculoskeletal radiologist. After a bri ...

THIEME MEDICAL PUBL INC2019

Validating atlas-based lesion disconnectomics in multiple sclerosis: A retrospective multi-centric study

Reto Meuli, Tobias Kober, Bénédicte Marie Maréchal, Jonas Richiardi

The translational potential of MR-based connectivity modelling is limited by the need for advanced diffusion imaging, which is not part of clinical protocols for many diseases. In addition, where diffusion data is available, brain connectivity analyses rel ...

2021

Functional Connectivity Eigennetworks Reveal Different Brain Dynamics In Multiple Sclerosis Patients

Dimitri Nestor Alice Van De Ville, Jonas Richiardi, Nora Leonardi

Resting state functional connectivity is defined as correlations in brain activity measured by functional magnetic resonance imaging without any stimulation paradigm. Such connectivity is dynamic, even over the course of minutes, and the development of too ...

Ieee2013

Static Models of Derivative-Coordinates Phase Spaces for Multivariate Time Series Classification: An Application to Signature Verification

Jonas Richiardi, Andrzej Drygajlo

Multivariate time series are sequences, whose order is provided by a time index; thus, most classifiers used on such data treat time as a special quantity, and encode it, structurally in a model. A typical example of such models is the hidden Markov model, ...

Springer-Verlag New York, Ms Ingrid Cunningham, 175 Fifth Ave, New York, Ny 10010 Usa2009

Shallow vs deep learning architectures for white matter lesion segmentation in the early stages of multiple sclerosis

Jean-Philippe Thiran, Tobias Kober, Meritxell Bach Cuadra, Cristina Granziera, Jonas Richiardi, Francesco La Rosa

In this work, we present a comparison of a shallow and a deep learning architecture for the automated segmentation of white matter lesions in MR images of multiple sclerosis patients. In particular, we train and test both methods on early stage disease pat ...

Springer2018

Principal components of functional connectivity: A new approach to study dynamic brain connectivity during rest

Dimitri Nestor Alice Van De Ville, Jonas Richiardi, Nora Leonardi

Functional connectivity (FC) as measured by correlation between NM BOLD time courses of distinct brain regions has revealed meaningful organization of spontaneous fluctuations in the resting brain. However, an increasing amount of evidence points to non-st ...

Elsevier2013

Cerebellar Connectomics Provide New Biomarkers in Early Multiple Sclerosis

Jean-Philippe Thiran, Dimitri Nestor Alice Van De Ville, Alessandro Daducci, Cristina Granziera, Gunnar Krüger, Djalel Eddine Meskaldji, Jonas Richiardi, Gloria Menegaz, David Paul Roger Romascano, Alexis Roche, Guillaume Bonnier, Ying-Chia Lin

The cerebellum is involved in multiple sclerosis (MS), but its implication in early phases is still poorly understood. We investigated structural and functional cerebellar connectivity alterations in early and minimally impaired MS patients, and their corr ...

2014