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Alexandre Bône
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2020 – today
- 2024
- [c19]Sisi Yang, Alexandre Bône, Thomas Decaens, Joan Alexis Glaunès:
Refining Deep Learning Segmentation Maps with a Local Thresholding Approach: Application to Liver Surface Nodularity Quantification in CT. CaPTion@MICCAI 2024: 104-113 - 2023
- [c18]Alexandre Bône, Marc-Michel Rohé:
Leveraging Multi-Phase CT for the Automatic Diagnosis of HCC with Deep Learning: Impacts of Lesion Localization and Phase Inclusion. ISBI 2023: 1-5 - [c17]Emma Sarfati, Alexandre Bône, Marc-Michel Rohé, Pietro Gori, Isabelle Bloch:
Learning to Diagnose Cirrhosis from Radiological and Histological Labels with Joint Self and Weakly-Supervised Pretraining Strategies. ISBI 2023: 1-4 - [c16]Noëlie Debs
, Alexandre Routier
Ensembling Voxel-Based and Box-Based Model Predictions for Robust Lesion Detection. AMAI@MICCAI 2023: 42-51 - [c15]Rebeca Vétil, Clément Abi Nader, Alexandre Bône, Marie-Pierre Vullierme, Marc-Michel Rohé, Pietro Gori, Isabelle Bloch:
Non-redundant Combination of Hand-Crafted and Deep Learning Radiomics: Application to the Early Detection of Pancreatic Cancer. CaPTion@MICCAI 2023: 68-82 - [c14]Emma Sarfati, Alexandre Bône, Marc-Michel Rohé, Pietro Gori, Isabelle Bloch:
Weakly-Supervised Positional Contrastive Learning: Application to Cirrhosis Classification. MICCAI (1) 2023: 227-237 - [i9]Emma Sarfati, Alexandre Bône, Marc-Michel Rohé, Pietro Gori, Isabelle Bloch:
Learning to diagnose cirrhosis from radiological and histological labels with joint self and weakly-supervised pretraining strategies. CoRR abs/2302.08427 (2023) - [i8]Emma Sarfati, Alexandre Bône, Marc-Michel Rohé, Pietro Gori, Isabelle Bloch:
Weakly-supervised positional contrastive learning: application to cirrhosis classification. CoRR abs/2307.04617 (2023) - [i7]Rebeca Vétil, Clément Abi Nader, Alexandre Bône, Marie-Pierre Vullierme, Marc-Michel Rohé, Pietro Gori, Isabelle Bloch:
Non-Redundant Combination of Hand-Crafted and Deep Learning Radiomics: Application to the Early Detection of Pancreatic Cancer. CoRR abs/2308.11389 (2023) - 2022
- [j4]Froso Sophocleous
Feasibility of a longitudinal statistical atlas model to study aortic growth in congenital heart disease. Comput. Biol. Medicine 144: 105326 (2022) - [j3]Anupama Goparaju, Krithika Iyer, Alexandre Bône
Benchmarking off-the-shelf statistical shape modeling tools in clinical applications. Medical Image Anal. 76: 102271 (2022) - [c13]Omar Ali, Alexandre Bône, Marc-Michel Rohé, Eric Vibert, Irene E. Vignon-Clementel:
Learning to Jointly Segment the Liver, Lesions and Vessels from Partially Annotated Datasets. ICIP 2022: 3626-3630 - [c12]Rebeca Vétil, Alexandre Bône, Marie-Pierre Vullierme, Marc-Michel Rohé, Pietro Gori, Isabelle Bloch:
Improving the Automatic Segmentation of Elongated Organs Using Geometrical Priors. ISBI 2022: 1-4 - [c11]Omar Ali, Alexandre Bône, Caterina Accardo
CoRe: An Automated Pipeline for the Prediction of Liver Resection Complexity from Preoperative CT Scans. AIIIMA/MIABID@MICCAI 2022: 125-133 - [c10]Rebeca Vétil, Clément Abi Nader, Alexandre Bône, Marie-Pierre Vullierme, Marc-Michel Rohé, Pietro Gori, Isabelle Bloch:
Learning Shape Distributions from Large Databases of Healthy Organs: Applications to Zero-Shot and Few-Shot Abnormal Pancreas Detection. MICCAI (2) 2022: 464-473 - [i6]Omar Ali, Alexandre Bône, Caterina Accardo
CoRe: An Automated Pipeline for The Prediction of Liver Resection Complexity from Preoperative CT Scans. CoRR abs/2210.08318 (2022) - [i5]Rebeca Vétil, Clément Abi Nader, Alexandre Bône, Marie-Pierre Vullierme, Marc-Michel Rohé, Pietro Gori, Isabelle Bloch:
Learning shape distributions from large databases of healthy organs: applications to zero-shot and few-shot abnormal pancreas detection. CoRR abs/2210.12095 (2022) - 2021
- [j2]Manon Ansart, Stéphane Epelbaum
Predicting the progression of mild cognitive impairment using machine learning: A systematic, quantitative and critical review. Medical Image Anal. 67: 101848 (2021) - [c9]Alexandre Bône, Samy Ammari, Jean-Philippe Lamarque, Mickael Elhaik, Emilie Chouzenoux, François Nicolas, Philippe Robert, Corinne Balleyguier, Nathalie Lassau, Marc-Michel Rohé:
Contrast-Enhanced Brain MRI Synthesis With Deep Learning: Key Input Modalities and Asymptotic Performance. ISBI 2021: 1159-1163 - 2020
- [b1]Alexandre Bône:
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). Sorbonne University, France, 2020 - [j1]Alexandre Bône
Learning the spatiotemporal variability in longitudinal shape data sets. Int. J. Comput. Vis. 128(12): 2873-2896 (2020) - [c8]Alexandre Bône, Paul Vernhet, Olivier Colliot
Learning Joint Shape and Appearance Representations with Metamorphic Auto-Encoders. MICCAI (1) 2020: 202-211 - [i4]Anupama Goparaju, Alexandre Bône, Nan Hu, Heath B. Henninger, Andrew E. Anderson, Stanley Durrleman, Matthijs Jacxsens, Alan Morris, Ibolya Csecs, Nassir Marrouche, Shireen Y. Elhabian:
Benchmarking off-the-shelf statistical shape modeling tools in clinical applications. CoRR abs/2009.02878 (2020)
2010 – 2019
- 2019
- [c7]Alexandre Bône
Auto-Encoding Meshes of any Topology with the Current-Splatting and Exponentiation Layers. ICCV Workshops 2019: 4014-4023 - [c6]Alexandre Bône
Learning Low-Dimensional Representations of Shape Data Sets with Diffeomorphic Autoencoders. IPMI 2019: 195-207 - [c5]Vianney Debavelaere, Alexandre Bône
Clustering of Longitudinal Shape Data Sets Using Mixture of Separate or Branching Trajectories. MICCAI (4) 2019: 66-74 - 2018
- [c4]Alexandre Bône
Learning Distributions of Shape Trajectories From Longitudinal Datasets: A Hierarchical Model on a Manifold of Diffeomorphisms. CVPR 2018: 9271-9280 - [c3]Alexandre Bône
Deformetrica 4: An Open-Source Software for Statistical Shape Analysis. ShapeMI@MICCAI 2018: 3-13 - [i3]Alexandre Bône, Olivier Colliot, Stanley Durrleman:
Learning distributions of shape trajectories from longitudinal datasets: a hierarchical model on a manifold of diffeomorphisms. CoRR abs/1803.10119 (2018) - 2017
- [c2]Maxime Louis, Alexandre Bône
Parallel Transport in Shape Analysis: A Scalable Numerical Scheme. GSI 2017: 29-37 - [c1]Alexandre Bône
Prediction of the Progression of Subcortical Brain Structures in Alzheimer's Disease from Baseline. GRAIL/MFCA/MICGen@MICCAI 2017: 101-113 - [i2]Alexandre Bône, Maxime Louis, Alexandre Routier, Jorge Samper-González, Michael Bacci, Benjamin Charlier, Olivier Colliot, Stanley Durrleman:
Prediction of the progression of subcortical brain structures in Alzheimer's disease from baseline. CoRR abs/1711.08716 (2017) - [i1]Maxime Louis, Alexandre Bône, Benjamin Charlier, Stanley Durrleman:
Parallel transport in shape analysis: a scalable numerical scheme. CoRR abs/1711.08725 (2017)
Coauthor Index
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last updated on 2024-10-17 20:32 CEST by the dblp team
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