Alexandre Bône
Orcid: 0000-0003-4442-3876
According to our database1,
Alexandre Bône
authored at least 24 papers
between 2017 and 2023.
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Bibliography
2023
Non-redundant Combination of Hand-Crafted and Deep Learning Radiomics: Application to the Early Detection of Pancreatic Cancer.
Proceedings of the Cancer Prevention Through Early Detection, 2023
Weakly-Supervised Positional Contrastive Learning: Application to Cirrhosis Classification.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023
Proceedings of the Applications of Medical Artificial Intelligence, 2023
Learning to Diagnose Cirrhosis from Radiological and Histological Labels with Joint Self and Weakly-Supervised Pretraining Strategies.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023
Leveraging Multi-Phase CT for the Automatic Diagnosis of HCC with Deep Learning: Impacts of Lesion Localization and Phase Inclusion.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023
2022
Benchmarking off-the-shelf statistical shape modeling tools in clinical applications.
Medical Image Anal., 2022
Feasibility of a longitudinal statistical atlas model to study aortic growth in congenital heart disease.
Comput. Biol. Medicine, 2022
Learning Shape Distributions from Large Databases of Healthy Organs: Applications to Zero-Shot and Few-Shot Abnormal Pancreas Detection.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022
CoRe: An Automated Pipeline for the Prediction of Liver Resection Complexity from Preoperative CT Scans.
Proceedings of the Artificial Intelligence over Infrared Images for Medical Applications and Medical Image Assisted Biomarker Discovery, 2022
Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022
Learning to Jointly Segment the Liver, Lesions and Vessels from Partially Annotated Datasets.
Proceedings of the 2022 IEEE International Conference on Image Processing, 2022
2021
Predicting the progression of mild cognitive impairment using machine learning: A systematic, quantitative and critical review.
Medical Image Anal., 2021
Contrast-Enhanced Brain MRI Synthesis With Deep Learning: Key Input Modalities and Asymptotic Performance.
Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021
2020
Learning adapted coordinate systems for the statistical analysis of anatomical shapes. Applications to Alzheimer's disease progression modeling. (Apprentissage de systèmes de coordonnées adaptés pour l'analyse statistique de formes anatomiques. Applications à la modélisation de la progression de la maladie d'Alzheimer).
PhD thesis, 2020
Int. J. Comput. Vis., 2020
Benchmarking off-the-shelf statistical shape modeling tools in clinical applications.
CoRR, 2020
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020
2019
Clustering of Longitudinal Shape Data Sets Using Mixture of Separate or Branching Trajectories.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019
Learning Low-Dimensional Representations of Shape Data Sets with Diffeomorphic Autoencoders.
Proceedings of the Information Processing in Medical Imaging, 2019
Auto-Encoding Meshes of any Topology with the Current-Splatting and Exponentiation Layers.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision Workshops, 2019
2018
Proceedings of the Shape in Medical Imaging, 2018
Learning Distributions of Shape Trajectories From Longitudinal Datasets: A Hierarchical Model on a Manifold of Diffeomorphisms.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018
2017
Prediction of the Progression of Subcortical Brain Structures in Alzheimer's Disease from Baseline.
Proceedings of the Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics, 2017
Proceedings of the Geometric Science of Information - Third International Conference, 2017