Hélène Urien

According to our database1, Hélène Urien authored at least 15 papers between 2016 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
Multi-Map Fusion for Weakly Supervised Disease Localization from Globally Assigned Diagnostic Labels in Brain MRI.
Proceedings of the 23rd IEEE International Symposium on Biomedical Imaging, 2026

2025
Deep-Learning Based Quality Assessment in Adaptive Optics Ophthalmoscopy Images.
Proceedings of the Fourteenth International Conference on Image Processing, 2025

Parkinson's Disease Detection on DaTscan Images Using Random Forest and Graph Deep Learning.
Proceedings of the 33rd European Signal Processing Conference, 2025

2024
<i>Where is VALDO?</i> VAscular Lesions Detection and segmentatiOn challenge at MICCAI 2021.
Medical Image Anal., January, 2024

Deep Neural Networks Comparison for MRI Segmentation of the Brainstem.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

Deep Learning-Based Segmentation of Retinal Vessels in Adaptive Optics Ophthalmoscopy Images.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

A Complete Method for the 3D Reconstruction of Axonal Pathways from 2 Orthogonal 3D OCT Images of the Lamina Cribrosa.
Proceedings of the IEEE International Conference on Acoustics, 2024

2023
3D Orthogonal SD-OCT Volumes Registration for the Enhancement of Pores in Lamina Cribrosa.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

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Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
Where is VALDO? VAscular Lesions Detection and segmentatiOn challenge at MICCAI 2021.
CoRR, 2022

Context-aware Attention U-Net for the segmentation of pores in Lamina Cribrosa using partial points annotation.
Proceedings of the 21st IEEE International Conference on Machine Learning and Applications, 2022

2020
Deep-learning based segmentation of challenging myelin sheaths.
Proceedings of the Tenth International Conference on Image Processing Theory, 2020

2018
The challenge of cerebral magnetic resonance imaging in neonates: A new method using mathematical morphology for the segmentation of structures including diffuse excessive high signal intensities.
Medical Image Anal., 2018

2017
Brain Lesion Detection in 3D PET Images Using Max-Trees and a New Spatial Context Criterion.
Proceedings of the Mathematical Morphology and Its Applications to Signal and Image Processing, 2017

2016
3D PET-driven multi-phase segmentation of meningiomas in MRI.
Proceedings of the 13th IEEE International Symposium on Biomedical Imaging, 2016


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