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Cortical lesions, central vein sign, and paramagnetic rim lesions in multiple sclerosis: Emerging machine learning techniques and future avenues

Publications associées (31)

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Predicting involuntary hospitalization in psychiatry: A machine learning investigation

Mehdi Gholam

Background Coercion in psychiatry is a controversial issue. Identifying its predictors and their interaction using traditional statistical methods is difficult, given the large number of variables involved. The purpose of this study was to use machine-lear ...

CAMBRIDGE UNIV PRESS2021

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

Meritxell Bach Cuadra, Tobias Kober, Reto Meuli, João Pedro Forjaco Jorge, Cristina Granziera, Francesco La Rosa, Jonas Richiardi, Mario Joao Fartaria de Oliveira

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

Model-informed machine learning for multi-component T2 relaxometry

Jean-Philippe Thiran, Meritxell Bach Cuadra, Tobias Kober, Tom Hilbert, Erick Jorge Canales Rodriguez, Elda Fischi Gomez, Gian Franco Piredda, Thomas Yu, Cristina Granziera, Muhamed Barakovic

Recovering the distribution from multi-echo magnetic resonance (MR) signals is challenging but has high potential as it provides biomarkers characterizing the tissue micro-structure, such as the myelin water fraction (MWF). In this work, we propose to comb ...

2020

Multiple sclerosis cortical and WM lesion segmentation at 3T MRI: a deep learning method based on FLAIR and MP2RAGE

Jean-Philippe Thiran, Meritxell Bach Cuadra, Cristina Granziera, Francesco La Rosa, Muhamed Barakovic, Mario Joao Fartaria de Oliveira, Ahmed Abdulkadir, Po-Jui Lu

The presence of cortical lesions in multiple sclerosis patients has emerged as an important biomarker of the disease. They appear in the earliest stages of the illness and have been shown to correlate with the severity of clinical symptoms. However, cortic ...

2020

Serum GFAP in multiple sclerosis: correlation with disease type and MRI markers of disease severity

Tobias Kober, Bénédicte Marie Maréchal, Mario Joao Fartaria de Oliveira, Ricardo Alberto Corredor Jerez

Neurofilament light chain (NfL) has been demonstrated to correlate with multiple sclerosis disease severity as well as treatment response. Nevertheless, additional serum biomarkers are still needed to better differentiate disease activity from disease prog ...

Nature Research2020

RimNet: A deep 3D multimodal MRI architecture for paramagnetic rim lesion assessment in multiple sclerosis

Meritxell Bach Cuadra, Tobias Kober, Francesco La Rosa, Cristina Granziera, Hamza Kebiri, Po-Jui Lu

Objectives In multiple sclerosis (MS), the presence of a paramagnetic rim at the edge of non-gadolinium-enhancing lesions indicates perilesional chronic inflammation. Patients featuring a higher paramagnetic rim lesion burden tend to have more aggressive d ...

2020

Evolution of Cortical and White Matter Lesion Load in Early-Stage Multiple Sclerosis: Correlation With Neuroaxonal Damage and Clinical Changes

Meritxell Bach Cuadra, Cristina Granziera, Guillaume Bonnier, Mario Joao Fartaria de Oliveira, Po-Jui Lu

Introduction:Changes in cortical and white matter lesion (CL, WML) load are pivotal metrics to diagnose and monitor multiple sclerosis patients. Yet, the relationship between (i) changes in CL/WML load and disease progression and between (ii) changes in CL ...

FRONTIERS MEDIA SA2020

Contrast-Enhanced Ultrasound Quantification: From Kinetic Modeling To Machine Learning

Marcel Arditi

Ultrasound contrast agents (UCAs) have opened up immense diagnostic possibilities by combined use of indicator dilution principles and dynamic contrast-enhanced ultrasound (DCE-US) imaging. UCAs are microbubbles encapsulated in a biocompatible shell. With ...

2020

Automated Detection and Segmentation of Multiple Sclerosis Lesions Using Ultra-High-Field MP2RAGE

Meritxell Bach Cuadra, Tobias Kober, Cristina Granziera, Mario Joao Fartaria de Oliveira, Kieran O'Brien

Objectives The aim of this study was to develop a new automated segmentation method of white matter (WM) and cortical multiple sclerosis (MS) lesions visible on magnetization-prepared 2 inversion-contrast rapid gradient echo (MP2RAGE) images acquired at 7 ...

LIPPINCOTT WILLIAMS & WILKINS2019

Differentiating Parkinson's disease motor subtypes using automated volume-based morphometry incorporating white matter and deep gray nuclear lesion load

Bénédicte Marie Maréchal

Background Periventricular leukoaraiosis may be an important pathological change in postural instability gait disorder (PIGD), a motor subtype of Parkinson's disease (PD). Clinical diagnosis of PIGD may be challenging for the general neurologist. Purpose T ...

2020

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Predicting involuntary hospitalization in psychiatry: A machine learning investigation

Mehdi Gholam

CAMBRIDGE UNIV PRESS2021

Serum GFAP in multiple sclerosis: correlation with disease type and MRI markers of disease severity

Tobias Kober, Bénédicte Marie Maréchal, Mario Joao Fartaria de Oliveira, Ricardo Alberto Corredor Jerez

Nature Research2020

Evolution of Cortical and White Matter Lesion Load in Early-Stage Multiple Sclerosis: Correlation With Neuroaxonal Damage and Clinical Changes

Meritxell Bach Cuadra, Cristina Granziera, Guillaume Bonnier, Mario Joao Fartaria de Oliveira, Po-Jui Lu

FRONTIERS MEDIA SA2020

Differentiating Parkinson's disease motor subtypes using automated volume-based morphometry incorporating white matter and deep gray nuclear lesion load

Bénédicte Marie Maréchal

2020

Contrast-Enhanced Ultrasound Quantification: From Kinetic Modeling To Machine Learning

Marcel Arditi

2020