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CVSnet: A machine learning approach for automated central vein sign assessment in multiple sclerosis
Related publications (37)
Development and clinical validation of computational imaging biomarkers for neurodegenerative diseases
Neurodegenerative and neuroinflammatory disorders often involve complex pathophysiological mechanisms that are â to this date â only partially understood. A more comprehensive understanding of those microstructural processes and their characterization ...
EPFL2024Multiparametric Characterization and Spatial Distribution of Different MS Lesion Phenotypes
Tobias Kober, Tom Hilbert, Gian Franco Piredda
BACKGROUND AND PURPOSE: MS lesions exhibit varying degrees of axonal and myelin damage. A comprehensive description of lesion phenotypes could contribute to an improved radiologic evaluation of smoldering inflammation and remyelination processes. This stud ...
Amer Soc Neuroradiology2024Few-shot Learning for Efficient and Effective Machine Learning Model Adaptation
Machine learning (ML) enables artificial intelligent (AI) agents to learn autonomously from data obtained from their environment to perform tasks. Modern ML systems have proven to be extremely effective, reaching or even exceeding human intelligence.Althou ...
EPFL2024A Multicenter Longitudinal MRI Study Assessing LeMan-PV Software Accuracy in the Detection of White Matter Lesions in Multiple Sclerosis Patients
Meritxell Bach Cuadra, Tobias Kober, Bénédicte Marie Maréchal, Cristina Granziera, Muhamed Barakovic, Lester Melie Garcia, Ricardo Alberto Corredor Jerez, Po-Jui Lu
BackgroundDetecting new and enlarged lesions in multiple sclerosis (MS) patients is needed to determine their disease activity. LeMan-PV is a software embedded in the scanner reconstruction system of one vendor, which automatically assesses new and enlarge ...
WILEY2023Brain microstructural and functional MRI: developments and application to a rat model of Alzheimer's disease
Magnetic resonance imaging (MRI) has been a valuable tool in investigating the pathological cascade of Alzheimer's disease (AD) and its progression, which are still open questions. Although some MRI-derived hallmarks in terms of functional connectivity and ...
EPFL2023EpilepsyNet: Interpretable Self-Supervised Seizure Detection for Low-Power Wearable Systems
David Atienza Alonso, Amir Aminifar, Renato Zanetti
Epilepsy is one of the most common neurological disorders that is characterized by recurrent and unpredictable seizures. Wearable systems can be used to detect the onset of a seizure and notify family members and emergency units for rescue. The majority of ...
2023Deep Learning Generalization with Limited and Noisy Labels
Deep neural networks have become ubiquitous in today's technological landscape, finding their way in a vast array of applications. Deep supervised learning, which relies on large labeled datasets, has been particularly successful in areas such as image cla ...
EPFL2023Accurate Diagnosis of Cortical and Infratentorial Lesions in Multiple Sclerosis Using Accelerated Fluid and White Matter Suppression Imaging
Objectives: The precise location of multiple sclerosis (MS) cortical lesions can be very challenging at 3 T, yet distinguishing them from subcortical lesions is essential for the diagnosis and prognosis of the disease. Compressed sensing-accelerated fluid ...
LIPPINCOTT WILLIAMS & WILKINS2023Streamline RimNet: Tools for Automatic Classification of Paramagnetic Rim Lesions in MRI of Multiple Sclerosis
Meritxell Bach Cuadra, Cristina Granziera, Francesco La Rosa, Maxence Charles F Wynen
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 ...
EPFL Infoscience2023Deep learning-based analysis of multiple sclerosis lesions with high and ultra-high field MRI
Multiple sclerosis (MS) is the most common demyelinating disease of the central nervous system and affects almost 3 million people worldwide. There is currently no cure for MS, and its symptoms, starting with fatigue and weakness, often progress over time ...
EPFL2022