Guiding the classification of hepatocellular carcinoma on 3D CT-scans using deep and handcrafted radiological features. - Sarfati, Emma; Bône, Alexandre; Rohé, Marc-Michel; Aubé, C.; Ronot, M.; Gori, Pietro; Bloch, Isabelle (CoRR, 2025)

Refining Deep Learning Segmentation Maps with a Local Thresholding Approach: Application to Liver Surface Nodularity Quantification in CT. - Yang, Sisi; Bône, Alexandre; Decaens, Thomas; Glaunès, Joan Alexis (2024)

Leveraging Multi-Phase CT for the Automatic Diagnosis of HCC with Deep Learning: Impacts of Lesion Localization and Phase Inclusion. - Bône, Alexandre; Rohé, Marc-Michel (2023)

Learning to Diagnose Cirrhosis from Radiological and Histological Labels with Joint Self and Weakly-Supervised Pretraining Strategies. - Sarfati, Emma; Bône, Alexandre; Rohé, Marc-Michel; Gori, Pietro; Bloch, Isabelle (2023)

Ensembling Voxel-Based and Box-Based Model Predictions for Robust Lesion Detection. - Debs, Noëlie; Routier, Alexandre; Nader, Clément Abi; Marcoux, Arnaud; Bône, Alexandre; Rohé, Marc-Michel (2023)

Non-redundant Combination of Hand-Crafted and Deep Learning Radiomics: Application to the Early Detection of Pancreatic Cancer. - Vétil, Rebeca; Nader, Clément Abi; Bône, Alexandre; Vullierme, Marie-Pierre; Rohé, Marc-Michel; Gori, Pietro; Bloch, Isabelle (2023)

Weakly-Supervised Positional Contrastive Learning: Application to Cirrhosis Classification. - Sarfati, Emma; Bône, Alexandre; Rohé, Marc-Michel; Gori, Pietro; Bloch, Isabelle (2023)

Learning to diagnose cirrhosis from radiological and histological labels with joint self and weakly-supervised pretraining strategies. - Sarfati, Emma; Bône, Alexandre; Rohé, Marc-Michel; Gori, Pietro; Bloch, Isabelle (CoRR, 2023)

Weakly-supervised positional contrastive learning: application to cirrhosis classification. - Sarfati, Emma; Bône, Alexandre; Rohé, Marc-Michel; Gori, Pietro; Bloch, Isabelle (CoRR, 2023)

Non-Redundant Combination of Hand-Crafted and Deep Learning Radiomics: Application to the Early Detection of Pancreatic Cancer. - Vétil, Rebeca; Nader, Clément Abi; Bône, Alexandre; Vullierme, Marie-Pierre; Rohé, Marc-Michel; Gori, Pietro; Bloch, Isabelle (CoRR, 2023)

Feasibility of a longitudinal statistical atlas model to study aortic growth in congenital heart disease. - Sophocleous, Froso; Bône, Alexandre; Shearn, Andrew I. U.; Forte, Mari Nieves Velasco; Bruse, Jan L.; Caputo, Massimo; Biglino, Giovanni (Comput. Biol. Medicine, 2022)

Benchmarking off-the-shelf statistical shape modeling tools in clinical applications. - Goparaju, Anupama; Iyer, Krithika; Bône, Alexandre; Hu, Nan; Henninger, Heath B.; Anderson, Andrew E.; Durrleman, Stanley; Jacxsens, Matthijs; Morris, Alan; Csecs, Ibolya; Marrouche, Nassir; Elhabian, Shireen Y. (Medical Image Anal., 2022)

Learning to Jointly Segment the Liver, Lesions and Vessels from Partially Annotated Datasets. - Ali, Omar; Bône, Alexandre; Rohé, Marc-Michel; Vibert, Eric; Vignon-Clementel, Irene E. (2022)

Improving the Automatic Segmentation of Elongated Organs Using Geometrical Priors. - Vétil, Rebeca; Bône, Alexandre; Vullierme, Marie-Pierre; Rohé, Marc-Michel; Gori, Pietro; Bloch, Isabelle (2022)

CoRe: An Automated Pipeline for the Prediction of Liver Resection Complexity from Preoperative CT Scans. - Ali, Omar; Bône, Alexandre; Accardo, Caterina; Belkouchi, Omar; Rohé, Marc-Michel; Vibert, Eric; Vignon-Clementel, Irene E. (2022)

Learning Shape Distributions from Large Databases of Healthy Organs: Applications to Zero-Shot and Few-Shot Abnormal Pancreas Detection. - Vétil, Rebeca; Nader, Clément Abi; Bône, Alexandre; Vullierme, Marie-Pierre; Rohé, Marc-Michel; Gori, Pietro; Bloch, Isabelle (2022)

CoRe: An Automated Pipeline for The Prediction of Liver Resection Complexity from Preoperative CT Scans. - Ali, Omar; Bône, Alexandre; Accardo, Caterina; Belkouchi, Omar; Rohé, Marc-Michel; Vibert, Eric; Vignon-Clementel, Irene E. (CoRR, 2022)

Learning shape distributions from large databases of healthy organs: applications to zero-shot and few-shot abnormal pancreas detection. - Vétil, Rebeca; Nader, Clément Abi; Bône, Alexandre; Vullierme, Marie-Pierre; Rohé, Marc-Michel; Gori, Pietro; Bloch, Isabelle (CoRR, 2022)

Predicting the progression of mild cognitive impairment using machine learning: A systematic, quantitative and critical review. - Ansart, Manon; Epelbaum, Stéphane; Bassignana, Giulia; Bône, Alexandre; Bottani, Simona; Cattai, Tiziana; Couronné, Raphaël; Faouzi, Johann; Koval, Igor; Louis, Maxime; Thibeau-Sutre, Elina; Wen, Junhao; et al. (Medical Image Anal., 2021)

Contrast-Enhanced Brain MRI Synthesis With Deep Learning: Key Input Modalities and Asymptotic Performance. - Bône, Alexandre; Ammari, Samy; Lamarque, Jean-Philippe; Elhaik, Mickael; Chouzenoux, Emilie; Nicolas, François; Robert, Philippe; Balleyguier, Corinne; Lassau, Nathalie; Rohé, Marc-Michel (2021)

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). - Bône, Alexandre (2020)

Learning the spatiotemporal variability in longitudinal shape data sets. - Bône, Alexandre; Colliot, Olivier; Durrleman, Stanley (Int. J. Comput. Vis., 2020)

Learning Joint Shape and Appearance Representations with Metamorphic Auto-Encoders. - Bône, Alexandre; Vernhet, Paul; Colliot, Olivier; Durrleman, Stanley (2020)

Benchmarking off-the-shelf statistical shape modeling tools in clinical applications. - Goparaju, Anupama; Bône, Alexandre; Hu, Nan; Henninger, Heath B.; Anderson, Andrew E.; Durrleman, Stanley; Jacxsens, Matthijs; Morris, Alan; Csecs, Ibolya; Marrouche, Nassir; Elhabian, Shireen Y. (CoRR, 2020)

Auto-Encoding Meshes of any Topology with the Current-Splatting and Exponentiation Layers. - Bône, Alexandre; Colliot, Olivier; Durrleman, Stanley (2019)

Learning Low-Dimensional Representations of Shape Data Sets with Diffeomorphic Autoencoders. - Bône, Alexandre; Louis, Maxime; Colliot, Olivier; Durrleman, Stanley (2019)

Clustering of Longitudinal Shape Data Sets Using Mixture of Separate or Branching Trajectories. - Debavelaere, Vianney; Bône, Alexandre; Durrleman, Stanley; Allassonnière, Stéphanie (2019)

Learning Distributions of Shape Trajectories From Longitudinal Datasets: A Hierarchical Model on a Manifold of Diffeomorphisms. - Bône, Alexandre; Colliot, Olivier; Durrleman, Stanley (2018)

Deformetrica 4: An Open-Source Software for Statistical Shape Analysis. - Bône, Alexandre; Louis, Maxime; Martin, Benoît; Durrleman, Stanley (2018)

Learning distributions of shape trajectories from longitudinal datasets: a hierarchical model on a manifold of diffeomorphisms. - Bône, Alexandre; Colliot, Olivier; Durrleman, Stanley (CoRR, 2018)

Parallel Transport in Shape Analysis: A Scalable Numerical Scheme. - Louis, Maxime; Bône, Alexandre; Charlier, Benjamin; Durrleman, Stanley (2017)

Prediction of the Progression of Subcortical Brain Structures in Alzheimer's Disease from Baseline. - Bône, Alexandre; Louis, Maxime; Routier, Alexandre; Samper-González, Jorge; Bacci, Michael; Charlier, Benjamin; Colliot, Olivier; Durrleman, Stanley (2017)

Prediction of the progression of subcortical brain structures in Alzheimer's disease from baseline. - Bône, Alexandre; Louis, Maxime; Routier, Alexandre; Samper-González, Jorge; Bacci, Michael; Charlier, Benjamin; Colliot, Olivier; Durrleman, Stanley (CoRR, 2017)

Parallel transport in shape analysis: a scalable numerical scheme. - Louis, Maxime; Bône, Alexandre; Charlier, Benjamin; Durrleman, Stanley (CoRR, 2017)