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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Fractal analysis in the quantification of medical imaging associated with multiple sclerosis pathology

Maria-Alexandra Paun

Backgrounds: Multiple sclerosis (MS) is an inveterate phlogistic situation characterized by focal and vaguely diffusive de-myelination and neurodegeneration, in the sphere of central nervous system (CNS). The brain's chronic inflammatory reaction includes ...

IMR PRESS2022

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

BMAT: An open-source BIDS managing and analysis tool

Meritxell Bach Cuadra, Francesco La Rosa, Maxence Charles F Wynen, Benoît Macq

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

Choreography Controlled (ChoCo) brain MRI artifact generation for labeled motion-corrupted datasets

Michel Kocher, François Lazeyras, Bastien Chopard, Sébastien Courvoisier, Julien Songeon

MRI is a non-invasive medical imaging modality that is sensitive to patient motion, which constitutes a major limitation in most clinical applications. Solutions may arise from the reduction of acquisition times or from motion-correction techniques, either ...

ELSEVIER SCI LTD2022

Graph Representation Learning in Computational Pathology

Guillaume Jaume

Advances in scanning systems have enabled the digitization of pathology slides into Whole-Slide Images (WSIs), opening up opportunities to develop Computational Pathology (CompPath) methods for computer-aided cancer diagnosis and prognosis. CompPath has be ...

EPFL2022

Automatic pathological speech assessment

Parvaneh Janbakhshi

Many pathologies cause impairments in the speech production mechanism resulting in reduced speech intelligibility and communicative ability. To assist the clinical diagnosis, treatment and management of speech disorders, automatic pathological speech asses ...

EPFL2022

Toward an objective assessment of mobility in clinical and daily activity settings

Arash Atrsaei

Quantification of mobility is the key to monitor the progression of mobility disorders as well as the effect of an intervention. Inertial measurement units (IMUs) with dedicated algorithms can quantify postural transitions and gait as the two key aspects o ...

EPFL2021

Quantitative Microstructural Imaging for Clinical Use

Gian Franco Piredda

Today, Magnetic Resonance Imaging (MRI) is a well-established medical imaging modality thanks to its excellent soft tissue contrast. Conventional MR image contrasts can be weighted towards one or more physical properties that discriminate different tissues ...

EPFL2021

MPRAGE to MP2RAGE UNI translation via generative adversarial network improves the automatic tissue and lesion segmentation in multiple sclerosis patients

Jean-Philippe Thiran, Meritxell Bach Cuadra, Thomas Yu, Cristina Granziera, Francesco La Rosa

Background and objective: Compared to the conventional magnetization-prepared rapid gradient-echo imaging (MPRAGE) MRI sequence, the specialized magnetization prepared 2 rapid acquisition gradient echoes (MP2RAGE) shows a higher brain tissue and lesion con ...

2021

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

Tobias Kober, Bénédicte Marie Maréchal, Reto Meuli, Jonas Richiardi, Mario Joao Fartaria de Oliveira

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

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MPRAGE to MP2RAGE UNI translation via generative adversarial network improves the automatic tissue and lesion segmentation in multiple sclerosis patients

Jean-Philippe Thiran, Meritxell Bach Cuadra, Thomas Yu, Cristina Granziera, Francesco La Rosa

2021

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

Tobias Kober, Bénédicte Marie Maréchal, Reto Meuli, Jonas Richiardi, Mario Joao Fartaria de Oliveira

2021