output
20142025
most citedExploring convolutional neural networks with transfer learning for diagnosing Lyme disease from skin lesion images

45 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions

12 papers

cs.CV2025

Stroke Lesion Segmentation in Clinical Workflows: A Modular, Lightweight, and Deployment-Ready Tool

Yann Kerverdo, Florent Leray, Youwan Mahé +2

Deep learning frameworks such as nnU-Net achieve state-of-the-art performance in brain lesion segmentation but remain difficult to deploy clinically due to heavy dependencies and m…

cs.CV2025

Unsupervised Deep Generative Models for Anomaly Detection in Neuroimaging: A Systematic Scoping Review

Youwan Mahé, Elise Bannier, Stéphanie Leplaideur +2

Unsupervised anomaly detection (UAD) based on deep generative modelling has been increasingly explored for identifying pathological brain abnormalities without requiring voxel-leve…

eess.IV2025★ 20 cited

Computer-aided shape features extraction and regression models for predicting the ascending aortic aneurysm growth rate

Leonardo Geronzi, Antonio Martinez, Michel Rochette +13

Objective: ascending aortic aneurysm growth prediction is still challenging in clinics. In this study, we evaluate and compare the ability of local and global shape features to pre…

physics.med-ph2022★ 9 cited

Measurement and Analysis of Lobar Lung Deformation After a Change of Patient Position During Video-Assisted Thoracoscopic Surgery

Pablo Alvarez, Matthieu Chabanas, Stéphane Sikora +3

Video-assisted thoracoscopic surgery (VATS) is a minimally invasive surgical technique for the diagnosis and treatment of early-stage lung cancer. During VATS, large lung deformati…

eess.IV2021★ 3 cited

Reproducibility and Evolution of Diffusion MRI Measurements within the Cervical Spinal Cord in Multiple Sclerosis

Haykel Snoussi, Emmanuel Caruyer, Benoit Combes +5

In Multiple Sclerosis (MS), there is a large discrepancy between the clinical observations and how the pathology is exhibited on brain images, this is known as the clinical-radiolo…

eess.IV2021★ 4 cited

Effectiveness of regional diffusion MRI measures in distinguishing multiple sclerosis abnormalities within the cervical spinal cord

Haykel Snoussi, Julien Cohen-Adad, Benoit Combes +5

Multiple sclerosis is an inflammatory disorder of the central nervous system. Quantitative MRI has huge potential to provide intrinsic and normative values of tissue properties use…

eess.IV2021★ 45 cited

Exploring convolutional neural networks with transfer learning for diagnosing Lyme disease from skin lesion images

Sk Imran Hossain, Jocelyn de Goër de Herve, Md Shahriar Hassan +16

Lyme disease which is one of the most common infectious vector-borne diseases manifests itself in most cases with erythema migrans (EM) skin lesions. Recent studies show that convo…

stat.AP2021

Reflection on modern methods: a note on variance estimation when using inverse probability weighting to handle attrition in cohort studies

Marie-Astrid Metten, Nathalie Costet, J. -F. Viel +1

The inverse probability weighting (IPW) method is used to handle attrition in association analyses derived from cohort studies. It consists in weighting the respondents at a given…

cs.AI2017★ 26 cited

Declarative Sequential Pattern Mining of Care Pathways

Thomas Guyet, André Happe, Yann Dauxais

Sequential pattern mining algorithms are widely used to explore care pathways database, but they generate a deluge of patterns, mostly redundant or useless. Clinicians need tools t…

q-bio.NC2017★ 6 cited

Multi-feature classifiers for burst detection in single EEG channels from preterm infants

X. Navarro, F. Porée, M. Kuchenbuch +3

The study of electroencephalographic (EEG) bursts in preterm infants provides valuable information about maturation or prognostication after perinatal asphyxia. Over the last two d…

q-bio.NC2016

Identification of interictal epileptic networks from dense-EEG

Mahmoud Hassan, Isabelle Merlet, Ahmad Mheich +4

Epilepsy is a network disease. The epileptic network usually involves spatially distributed brain regions. In this context, noninvasive M/EEG source connectivity is an emerging tec…

math-ph2014

Evaluation of an ensemble-based incremental variational data assimilation

Yin Yang, Cordelia Robinson, Dominique Heitz +1

In this work, we aim at studying ensemble based optimal control strategies for data assimilation. Such formulation nicely combines the ingredients of ensemble Kalman filters and va…