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Publications of year 2022

Thesis

  1. Yann Thanwerdas. Riemannian and stratified geometries of covariance and correlation matrices. Theses, Université Côte d'Azur, May 2022. Keyword(s): Riemannian geometry, Covariance matrices, Correlation matrices, Families of metrics, Geodesics, Stratified spaces., Géométrie riemannienne, Matrices de covariance, Matrices de corrélation, Familles de métriques, Géodésiques, Espaces stratifiés..
    @phdthesis{thanwerdas:tel-03698752,
    TITLE = {{Riemannian and stratified geometries of covariance and correlation matrices}},
    AUTHOR = {Thanwerdas, Yann},
    url-hal= {https://hal.archives-ouvertes.fr/tel-03698752},
    SCHOOL = {{Universit{\'e} C{\^o}te d'Azur}},
    YEAR = {2022},
    MONTH = May,
    KEYWORDS = {Riemannian geometry ; Covariance matrices ; Correlation matrices ; Families of metrics ; Geodesics ; Stratified spaces. ; G{\'e}om{\'e}trie riemannienne ; Matrices de covariance ; Matrices de corr{\'e}lation ; Familles de m{\'e}triques ; G{\'e}od{\'e}siques ; Espaces stratifi{\'e}s.},
    TYPE = {Theses},
    PDF = {https://hal.archives-ouvertes.fr/tel-03698752/file/Thanwerdas_PhD.pdf},
    HAL_ID = {tel-03698752},
    HAL_VERSION = {v1},
    
    }
    


Articles in journal, book chapters

  1. Clément Abi Nader, Federica Ribaldi, Giovanni B Frisoni, Valentina Garibotto, Philippe Robert, Nicholas Ayache, and Marco Lorenzi. SimulAD: A dynamical model for personalized simulation and disease staging in Alzheimer's disease. Neurobiology of Aging, 113:73-83, May 2022. Keyword(s): Alzheimer's disease, Disease progression models, Clinical trials, Biomarkers.
    @article{abinader:hal-03514292,
    TITLE = {{SimulAD: A dynamical model for personalized simulation and disease staging in Alzheimer's disease}},
    AUTHOR = {Abi Nader, Cl{\'e}ment and Ribaldi, Federica and Frisoni, Giovanni B and Garibotto, Valentina and Robert, Philippe and Ayache, Nicholas and Lorenzi, Marco},
    url-hal= {https://hal.inria.fr/hal-03514292},
    JOURNAL = {{Neurobiology of Aging}},
    PUBLISHER = {{Elsevier}},
    VOLUME = {113},
    PAGES = {73-83},
    YEAR = {2022},
    MONTH = May,
    DOI = {10.1016/j.neurobiolaging.2021.12.015},
    KEYWORDS = {Alzheimer's disease ; Disease progression models ; Clinical trials ; Biomarkers},
    PDF = {https://hal.inria.fr/hal-03514292/file/nboa_2021_final.pdf},
    HAL_ID = {hal-03514292},
    HAL_VERSION = {v1},
    
    }
    


  2. Benoît Audelan, Dimitri Hamzaoui, Sarah Montagne, Raphaële Renard-Penna, and Hervé Delingette. Robust Bayesian fusion of continuous segmentation maps. Medical Image Analysis, 78:102398, May 2022. Keyword(s): Image segmentation, Data fusion, Consensus, Mixture.
    @article{audelan:hal-03594219,
    TITLE = {{Robust Bayesian fusion of continuous segmentation maps}},
    AUTHOR = {Audelan, Beno{\^i}t and Hamzaoui, Dimitri and Montagne, Sarah and Renard-Penna, Rapha{\"e}le and Delingette, Herv{\'e}},
    url-hal= {https://hal.inria.fr/hal-03594219},
    JOURNAL = {{Medical Image Analysis}},
    PUBLISHER = {{Elsevier}},
    VOLUME = {78},
    PAGES = {102398},
    YEAR = {2022},
    MONTH = May,
    DOI = {10.1016/j.media.2022.102398},
    KEYWORDS = {Image segmentation ; Data fusion ; Consensus ; Mixture},
    PDF = {https://hal.inria.fr/hal-03594219/file/manuscript.pdf},
    HAL_ID = {hal-03594219},
    HAL_VERSION = {v1},
    
    }
    


  3. Nicholas Ayache. La fée IA au chevet des malades. Pour la Science. Dossier, 115(115):18-23, May 2022. Note: The article is available at the following address: https://www.pourlascience.fr/sd/medecine/la-fee-ia-au-chevet-des-malades-23684.php.
    @article{ayache:hal-03689197,
    TITLE = {{La f{\'e}e IA au chevet des malades}},
    AUTHOR = {Ayache, Nicholas},
    url-hal= {https://hal.archives-ouvertes.fr/hal-03689197},
    NOTE = {The article is available at the following address: https://www.pourlascience.fr/sd/medecine/la-fee-ia-au-chevet-des-malades-23684.php},
    JOURNAL = {{Pour la Science. Dossier}},
    PUBLISHER = {{Belin}},
    SERIES = {''Jusqu'o{\`u} ira l'intelligence artificielle ?''},
    VOLUME = {115},
    NUMBER = {115},
    PAGES = {18-23},
    YEAR = {2022},
    MONTH = May,
    HAL_ID = {hal-03689197},
    HAL_VERSION = {v1},
    
    }
    


  4. Tania Marina Bacoyannis, Buntheng Ly, H Cochet, and Maxime Sermesant. Deep learning formulation of ECGI evaluated on clinical data. EP-Europace, 24(Supplement_1), May 2022. Keyword(s): Electrocardiography, Inverse Problem, Deep learning, Computational Modelling, Generative Model, Data Processing, Clinical Evaluation.
    @article{bacoyannis:hal-03739242,
    TITLE = {{Deep learning formulation of ECGI evaluated on clinical data}},
    AUTHOR = {Bacoyannis, Tania Marina and Ly, Buntheng and Cochet, H and Sermesant, Maxime},
    url-hal= {https://hal.inria.fr/hal-03739242},
    JOURNAL = {{EP-Europace}},
    PUBLISHER = {{Oxford University Press (OUP)}},
    VOLUME = {24},
    NUMBER = {Supplement\_1},
    YEAR = {2022},
    MONTH = May,
    DOI = {10.1093/europace/euac053.566},
    KEYWORDS = {Electrocardiography ; Inverse Problem ; Deep learning ; Computational Modelling ; Generative Model ; Data Processing ; Clinical Evaluation},
    HAL_ID = {hal-03739242},
    HAL_VERSION = {v1},
    
    }
    


  5. Irene Balelli, Santiago Silva, and Marco Lorenzi. A Differentially Private Probabilistic Framework for Modeling the Variability Across Federated Datasets of Heterogeneous Multi-View Observations. Journal of Machine Learning for Biomedical Imaging, April 2022.
    @article{balelli:hal-03644819,
    TITLE = {{A Differentially Private Probabilistic Framework for Modeling the Variability Across Federated Datasets of Heterogeneous Multi-View Observations}},
    AUTHOR = {Balelli, Irene and Silva, Santiago and Lorenzi, Marco},
    url-hal= {https://hal.inria.fr/hal-03644819},
    JOURNAL = {{Journal of Machine Learning for Biomedical Imaging}},
    PUBLISHER = {{Melba editors}},
    YEAR = {2022},
    MONTH = Apr,
    HAL_ID = {hal-03644819},
    HAL_VERSION = {v1},
    
    }
    


  6. James Benn and Stephen Marsland. The Measurement and Analysis of Shapes. Annals of Global Analysis and Geometry, April 2022. Keyword(s): Shape, Currents, Hodge theory, Sobolev diffeomorphisms, Euler Equations, Probability densities.
    @article{benn:hal-03556752,
    TITLE = {{The Measurement and Analysis of Shapes}},
    AUTHOR = {Benn, James and Marsland, Stephen},
    url-hal= {https://hal.archives-ouvertes.fr/hal-03556752},
    JOURNAL = {{Annals of Global Analysis and Geometry}},
    PUBLISHER = {{Springer Verlag}},
    YEAR = {2022},
    MONTH = Apr,
    DOI = {10.1007/s10455-022-09839-z},
    KEYWORDS = {Shape ; Currents ; Hodge theory ; Sobolev diffeomorphisms ; Euler Equations ; Probability densities},
    PDF = {https://hal.archives-ouvertes.fr/hal-03556752/file/Revision3F.pdf},
    HAL_ID = {hal-03556752},
    HAL_VERSION = {v1},
    
    }
    


  7. Hind Dadoun, Anne-Laure Rousseau, Eric de Kerviler, Jean Michel Correas, Anne-Marie Tissier, Fanny Joujou, Sylvain Bodard, Kemel Khezzane, Constance de Margerie-Mellon, Hervé Delingette, and Nicholas Ayache. Detection, Localization, and Characterization of Focal Liver Lesions in Abdominal US with Deep Learning. Radiology: Artificial Intelligence, 2022.
    @article{dadoun:hal-03583297,
    TITLE = {{Detection, Localization, and Characterization of Focal Liver Lesions in Abdominal US with Deep Learning}},
    AUTHOR = {Dadoun, Hind and Rousseau, Anne-Laure and de Kerviler, Eric and Correas, Jean Michel and Tissier, Anne-Marie and Joujou, Fanny and Bodard, Sylvain and Khezzane, Kemel and de Margerie-Mellon, Constance and Delingette, Herv{\'e} and Ayache, Nicholas},
    url-hal= {https://hal.inria.fr/hal-03583297},
    JOURNAL = {{Radiology: Artificial Intelligence}},
    PUBLISHER = {{RSNA}},
    YEAR = {2022},
    DOI = {10.1148/ryai.210110},
    HAL_ID = {hal-03583297},
    HAL_VERSION = {v1},
    
    }
    


  8. Nicolas Guigui and Xavier Pennec. Numerical Accuracy of Ladder Schemes for Parallel Transport on Manifolds. Foundations of Computational Mathematics, 22:757-790, June 2022.
    @article{guigui:hal-02894783,
    TITLE = {{Numerical Accuracy of Ladder Schemes for Parallel Transport on Manifolds}},
    AUTHOR = {Guigui, Nicolas and Pennec, Xavier},
    url-hal= {https://hal.inria.fr/hal-02894783},
    JOURNAL = {{Foundations of Computational Mathematics}},
    PUBLISHER = {{Springer Verlag}},
    VOLUME = {22},
    PAGES = {757-790},
    YEAR = {2022},
    MONTH = Jun,
    DOI = {10.1007/s10208-021-09515-x},
    PDF = {https://hal.inria.fr/hal-02894783v3/file/Guigui_et_al-2021-Foundations_of_Computational_Mathematics.pdf},
    HAL_ID = {hal-02894783},
    HAL_VERSION = {v3},
    
    }
    


  9. Dimitri Hamzaoui, Sarah Montagne, Benjamin Granger, Alexandre Allera, Malek Ezziane, Anna Luzurier, Raphaële Quint, Mehdi Kalai, Nicholas Ayache, Hervé Delingette, and Raphaele Renard-Penna. Prostate volume prediction on MRI: tools, accuracy and variability. European Radiology, February 2022. Note: The original publication is available at www.springerlink.com: https://link.springer.com/article/10.1007/s00330-022-08554-4. Keyword(s): Prostate, Magnetic Resonance Imaging, Volume, PSA density, Segmentation.
    @article{hamzaoui:hal-03409262,
    TITLE = {{Prostate volume prediction on MRI: tools, accuracy and variability}},
    AUTHOR = {Hamzaoui, Dimitri and Montagne, Sarah and Granger, Benjamin and Allera, Alexandre and Ezziane, Malek and Luzurier, Anna and Quint, Rapha{\"e}le and Kalai, Mehdi and Ayache, Nicholas and Delingette, Herv{\'e} and Renard-Penna, Raphaele},
    url-hal= {https://hal.archives-ouvertes.fr/hal-03409262},
    NOTE = {The original publication is available at www.springerlink.com: https://link.springer.com/article/10.1007/s00330-022-08554-4},
    JOURNAL = {{European Radiology}},
    PUBLISHER = {{Springer Verlag}},
    YEAR = {2022},
    MONTH = Feb,
    DOI = {10.1007/s00330-022-08554-4},
    KEYWORDS = {Prostate ; Magnetic Resonance Imaging ; Volume ; PSA density ; Segmentation},
    PDF = {https://hal.archives-ouvertes.fr/hal-03409262/file/EURA-D-21-03295_R1-16-47.pdf},
    HAL_ID = {hal-03409262},
    HAL_VERSION = {v1},
    
    }
    


  10. Dimitri Hamzaoui, Sarah Montagne, Raphaele Renard-Penna, Nicholas Ayache, and Hervé Delingette. Automatic Zonal Segmentation of the Prostate from 2D and 3D T2-weighted MRI and Evaluation for Clinical Use. Journal of Medical Imaging, 9(2):024001, March 2022. Keyword(s): Prostate, Segmentation, Deep Learning, Lesion, Magnetic Resonance Imaging, Inter-rater Variability.
    @article{hamzaoui:hal-03587074,
    TITLE = {{Automatic Zonal Segmentation of the Prostate from 2D and 3D T2-weighted MRI and Evaluation for Clinical Use}},
    AUTHOR = {Hamzaoui, Dimitri and Montagne, Sarah and Renard-Penna, Raphaele and Ayache, Nicholas and Delingette, Herv{\'e}},
    url-hal= {https://hal.archives-ouvertes.fr/hal-03587074},
    JOURNAL = {{Journal of Medical Imaging}},
    PUBLISHER = {{SPIE Digital Library}},
    VOLUME = {9},
    NUMBER = {2},
    PAGES = {024001},
    YEAR = {2022},
    MONTH = Mar,
    DOI = {10.1117/1.JMI.9.2.024001},
    KEYWORDS = {Prostate ; Segmentation ; Deep Learning ; Lesion ; Magnetic Resonance Imaging ; Inter-rater Variability},
    PDF = {https://hal.archives-ouvertes.fr/hal-03587074v2/file/JMI-21261R_online.pdf},
    HAL_ID = {hal-03587074},
    HAL_VERSION = {v2},
    
    }
    


  11. Marius Ilie, Jonathan Benzaquen, Paul Tourniaire, Simon Heeke, Nicholas Ayache, Hervé Delingette, Elodie Long-Mira, Sandra Lassalle, Marame Hamila, Julien Fayada, Josiane Otto, Charlotte Cohen, Abel Gomez Caro, Jean Philippe Berthet, Charles Hugo Marquette, Véronique Hofman, Christophe Bontoux, and Paul Hofman. Deep learning facilitates distinguishing histologic subtypes of pulmonary neuroendocrine tumors on digital whole-slide images. Cancers, 14(7):1740, March 2022. Keyword(s): lung, neuroendocrine carcinoma, deep learning, CNN, HALO-AI.
    @article{ilie:hal-03621585,
    TITLE = {{Deep learning facilitates distinguishing histologic subtypes of pulmonary neuroendocrine tumors on digital whole-slide images}},
    AUTHOR = {Ilie, Marius and Benzaquen, Jonathan and Tourniaire, Paul and Heeke, Simon and Ayache, Nicholas and Delingette, Herv{\'e} and Long-Mira, Elodie and Lassalle, Sandra and Hamila, Marame and Fayada, Julien and Otto, Josiane and Cohen, Charlotte and Gomez Caro, Abel and Berthet, Jean Philippe and Marquette, Charles Hugo and Hofman, V{\'e}ronique and Bontoux, Christophe and Hofman, Paul},
    url-hal= {https://hal.inria.fr/hal-03621585},
    JOURNAL = {{Cancers}},
    PUBLISHER = {{MDPI}},
    VOLUME = {14},
    NUMBER = {7},
    PAGES = {1740},
    YEAR = {2022},
    MONTH = Mar,
    DOI = {10.3390/cancers14071740},
    KEYWORDS = {lung ; neuroendocrine carcinoma ; deep learning ; CNN ; HALO-AI},
    HAL_ID = {hal-03621585},
    HAL_VERSION = {v1},
    
    }
    


  12. Yann Thanwerdas and Xavier Pennec. The geometry of mixed-Euclidean metrics on symmetric positive definite matrices. Differential Geometry and its Applications, 81(101867), April 2022. Keyword(s): Symmetric Positive Definite matrices, Riemannian geometry, information geometry, families of metrics, kernel metrics, alpha-Procrustes, mixed-power-Euclidean, mixed-Euclidean, (u, v)-divergence, ($\alpha$, $\beta$)-divergence, 15B48, 53B12, 15A63, 53B20.
    @article{thanwerdas:hal-03414887,
    TITLE = {{The geometry of mixed-Euclidean metrics on symmetric positive definite matrices}},
    AUTHOR = {Thanwerdas, Yann and Pennec, Xavier},
    url-hal= {https://hal.archives-ouvertes.fr/hal-03414887},
    JOURNAL = {{Differential Geometry and its Applications}},
    PUBLISHER = {{Elsevier}},
    VOLUME = {81},
    NUMBER = {101867},
    YEAR = {2022},
    MONTH = Apr,
    DOI = {10.1016/j.difgeo.2022.101867},
    KEYWORDS = {Symmetric Positive Definite matrices ; Riemannian geometry ; information geometry ; families of metrics ; kernel metrics ; alpha-Procrustes ; mixed-power-Euclidean ; mixed-Euclidean ; (u ; v)-divergence ; ($\alpha$ ; $\beta$)-divergence ; 15B48 ; 53B12 ; 15A63 ; 53B20},
    PDF = {https://hal.archives-ouvertes.fr/hal-03414887/file/main.pdf},
    HAL_ID = {hal-03414887},
    HAL_VERSION = {v1},
    
    }
    


  13. Nicolas Guigui and Xavier Pennec. Parallel transport, a central tool in geometric statistics for computational anatomy: Application to cardiac motion modeling. In Geometry and Statistics, volume 46 of Handbook of Statistics. Elsevier, May 2022. Keyword(s): Parallel transport, longitudinal studies, mean trajectory, cardiac motion analysis, Schild's ladder, pole ladder, Riemannian manifolds.
    @incollection{guigui:hal-03684811,
    TITLE = {{Parallel transport, a central tool in geometric statistics for computational anatomy: Application to cardiac motion modeling}},
    AUTHOR = {Guigui, Nicolas and Pennec, Xavier},
    url-hal= {https://hal.inria.fr/hal-03684811},
    BOOKTITLE = {{Geometry and Statistics}},
    PUBLISHER = {{Elsevier}},
    SERIES = {Handbook of Statistics},
    VOLUME = {46},
    YEAR = {2022},
    MONTH = May,
    DOI = {10.1016/bs.host.2022.03.006},
    KEYWORDS = {Parallel transport ; longitudinal studies ; mean trajectory ; cardiac motion analysis ; Schild's ladder ; pole ladder ; Riemannian manifolds},
    PDF = {https://hal.inria.fr/hal-03684811/file/H0S_ParallelTransport.pdf},
    HAL_ID = {hal-03684811},
    HAL_VERSION = {v1},
    
    }
    


Conference articles

  1. Yann Fraboni, Richard Vidal, Laetitia Kameni, and Marco Lorenzi. A General Theory for Client Sampling in Federated Learning. In IJCAI 2022 - 31st International joint conférence on artificial intellignce, Vienna, Austria, July 2022.
    @inproceedings{fraboni:hal-03500307,
    TITLE = {{A General Theory for Client Sampling in Federated Learning}},
    AUTHOR = {Fraboni, Yann and Vidal, Richard and Kameni, Laetitia and Lorenzi, Marco},
    url-hal= {https://hal.archives-ouvertes.fr/hal-03500307},
    BOOKTITLE = {{IJCAI 2022 - 31st International joint conf{\'e}rence on artificial intellignce}},
    ADDRESS = {Vienna, Austria},
    YEAR = {2022},
    MONTH = Jul,
    PDF = {https://hal.archives-ouvertes.fr/hal-03500307v2/file/A_General_Theory_for_Client_Sampling_in_Federated_Learning.pdf},
    HAL_ID = {hal-03500307},
    HAL_VERSION = {v2},
    
    }
    


  2. Dimitri Hamzaoui, Sarah Montagne, Raphaele Renard-Penna, Nicholas Ayache, and Hervé Delingette. MOrphologically-aware Jaccard-based ITerative Optimization (MOJITO) for Consensus Segmentation. In UNSURE 2022: Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, Singapore, Singapore, September 2022. Keyword(s): Consensus Algorithm, Segmentation 2D et 3D, Jaccard distance, STAPLE.
    @inproceedings{hamzaoui:hal-03775967,
    TITLE = {{MOrphologically-aware Jaccard-based ITerative Optimization (MOJITO) for Consensus Segmentation}},
    AUTHOR = {Hamzaoui, Dimitri and Montagne, Sarah and Renard-Penna, Raphaele and Ayache, Nicholas and Delingette, Herv{\'e}},
    url-hal= {https://hal.archives-ouvertes.fr/hal-03775967},
    BOOKTITLE = {{UNSURE 2022: Uncertainty for Safe Utilization of Machine Learning in Medical Imaging}},
    ADDRESS = {Singapore, Singapore},
    YEAR = {2022},
    MONTH = Sep,
    KEYWORDS = {Consensus Algorithm ; Segmentation 2D et 3D ; Jaccard distance ; STAPLE},
    HAL_ID = {hal-03775967},
    HAL_VERSION = {v1},
    
    }
    


  3. Victoriya Kashtanova, Ibrahim Ayed, Andony Arrieula, Mark Potse, Patrick Gallinari, and Maxime Sermesant. Deep Learning for Model Correction in Cardiac Electrophysiological Imaging. In MIDL 2022 - Medical Imaging with Deep Learning, Zurich, Switzerland, July 2022. Keyword(s): Electrophysiology, Deep learning, Simulations, Physics-based learning.
    @inproceedings{kashtanova:hal-03687596,
    TITLE = {{Deep Learning for Model Correction in Cardiac Electrophysiological Imaging}},
    AUTHOR = {Kashtanova, Victoriya and Ayed, Ibrahim and Arrieula, Andony and Potse, Mark and Gallinari, Patrick and Sermesant, Maxime},
    url-hal= {https://hal.archives-ouvertes.fr/hal-03687596},
    BOOKTITLE = {{MIDL 2022 - Medical Imaging with Deep Learning}},
    ADDRESS = {Zurich, Switzerland},
    YEAR = {2022},
    MONTH = Jul,
    KEYWORDS = {Electrophysiology ; Deep learning ; Simulations ; Physics-based learning},
    PDF = {https://hal.archives-ouvertes.fr/hal-03687596/file/Kashtanova_MIDL22_Camera_Ready.pdf},
    HAL_ID = {hal-03687596},
    HAL_VERSION = {v1},
    
    }
    


  4. Huiyu Li, Nicholas Ayache, and Hervé Delingette. Data Stealing Attack on Medical Images: Is it Safe to Export Networks from Data Lakes?. In MICCAI Workshop on Distributed, Collaborative and Federated Learning, Singapore, Singapore, September 2022. Keyword(s): Data Stealing Attack, Privacy, Medical Images.
    @inproceedings{li:hal-03775940,
    TITLE = {{Data Stealing Attack on Medical Images: Is it Safe to Export Networks from Data Lakes?}},
    AUTHOR = {Li, Huiyu and Ayache, Nicholas and Delingette, Herv{\'e}},
    url-hal= {https://hal.inria.fr/hal-03775940},
    BOOKTITLE = {{MICCAI Workshop on Distributed, Collaborative and Federated Learning}},
    ADDRESS = {Singapore, Singapore},
    YEAR = {2022},
    MONTH = Sep,
    KEYWORDS = {Data Stealing Attack ; Privacy ; Medical Images},
    PDF = {https://hal.inria.fr/hal-03775940/file/Paper.pdf},
    HAL_ID = {hal-03775940},
    HAL_VERSION = {v1},
    
    }
    


  5. Riccardo Taiello, Melek Önen, Olivier Humbert, and Marco Lorenzi. Privacy Preserving Image Registration. In Medical Image Computing and Computer Assisted Intervention -- MICCAI 2022, Singapore, Singapore, September 2022. Keyword(s): Image Registration, Privacy enhancing technologies, Trustworthiness.
    @inproceedings{taiello:hal-03697446,
    TITLE = {{Privacy Preserving Image Registration}},
    AUTHOR = {Taiello, Riccardo and {\"O}nen, Melek and Humbert, Olivier and Lorenzi, Marco},
    url-hal= {https://hal.inria.fr/hal-03697446},
    BOOKTITLE = {{Medical Image Computing and Computer Assisted Intervention -- MICCAI 2022}},
    ADDRESS = {Singapore, Singapore},
    YEAR = {2022},
    MONTH = Sep,
    KEYWORDS = {Image Registration ; Privacy enhancing technologies ; Trustworthiness},
    PDF = {https://hal.inria.fr/hal-03697446v3/file/Privacy_Preserving_Image_Registration.pdf},
    HAL_ID = {hal-03697446},
    HAL_VERSION = {v3},
    
    }
    


Miscellaneous

  1. Francisco J Burgos-Fernandez, Buntheng Ly, Fernando Dìaz-Doutón, Meritxell Vilaseca, Jaume Pujol, and Maxime Sermesant. Deep learning for eye fundus diagnosis based on multispectral imaging. ARVO 2022 - Annual meeting of the Association for Research in Vision and Ophthalmology, May 2022. Note: Poster.
    @misc{burgosfernandez:hal-03695867,
    TITLE = {{Deep learning for eye fundus diagnosis based on multispectral imaging}},
    AUTHOR = {Burgos-Fernandez, Francisco J and Ly, Buntheng and D{\'i}az-Dout{\'o}n, Fernando and Vilaseca, Meritxell and Pujol, Jaume and Sermesant, Maxime},
    url-hal= {https://hal.inria.fr/hal-03695867},
    NOTE = {Poster},
    HOWPUBLISHED = {{ARVO 2022 - Annual meeting of the Association for Research in Vision and Ophthalmology}},
    YEAR = {2022},
    MONTH = May,
    PDF = {https://hal.inria.fr/hal-03695867/file/ARVO2022_Abstract_FranciscoJBurgos.pdf},
    HAL_ID = {hal-03695867},
    HAL_VERSION = {v1},
    
    }
    


  2. Hind Dadoun, Hervé Delingette, Anne-Laure Rousseau, Eric de Kerviler, and Nicholas Ayache. Deep Clustering for Abdominal Organ Classification in US imaging. Note: Working paper or preprint, June 2022. Keyword(s): ultrasound imaging, representation learning, deep clustering, semi-supervised learning.
    @unpublished{dadoun:hal-03773082,
    TITLE = {{Deep Clustering for Abdominal Organ Classification in US imaging}},
    AUTHOR = {Dadoun, Hind and Delingette, Herv{\'e} and Rousseau, Anne-Laure and de Kerviler, Eric and Ayache, Nicholas},
    url-hal= {https://hal.inria.fr/hal-03773082},
    NOTE = {working paper or preprint},
    YEAR = {2022},
    MONTH = Jun,
    KEYWORDS = {ultrasound imaging ; representation learning ; deep clustering ; semi-supervised learning},
    PDF = {https://hal.inria.fr/hal-03773082v3/file/soumission_jmi_dadoun_vf.pdf},
    HAL_ID = {hal-03773082},
    HAL_VERSION = {v3},
    
    }
    


  3. Yann Fraboni, Richard Vidal, Laetitia Kameni, and Marco Lorenzi. A General Theory for Federated Optimization with Asynchronous and Heterogeneous Clients Updates. Note: Working paper or preprint, July 2022.
    @unpublished{fraboni:hal-03720629,
    TITLE = {{A General Theory for Federated Optimization with Asynchronous and Heterogeneous Clients Updates}},
    AUTHOR = {Fraboni, Yann and Vidal, Richard and Kameni, Laetitia and Lorenzi, Marco},
    url-hal= {https://hal.archives-ouvertes.fr/hal-03720629},
    NOTE = {working paper or preprint},
    YEAR = {2022},
    MONTH = Jul,
    PDF = {https://hal.archives-ouvertes.fr/hal-03720629/file/A_General_Theory_for_Federated_Optimization_with_Delayed_Gradients_and_Heterogeneous_Data.pdf},
    HAL_ID = {hal-03720629},
    HAL_VERSION = {v1},
    
    }
    


  4. Yann Thanwerdas and Xavier Pennec. Theoretically and computationally convenient geometries on full-rank correlation matrices. Note: Working paper or preprint, January 2022. Keyword(s): SPD matrices, Correlation matrices, Lie group, Lie group actions, Quotient-affine metric, Lie-Cholesky metrics, Poly-hyperbolic-Cholesky metrics, Euclidean-Cholesky metrics, Log-Euclidean-Cholesky metrics, 15B48, 15B99, 53-08, 53B21, 15A63, 53C22, 62H20, 58D17.
    @unpublished{thanwerdas:hal-03527072,
    TITLE = {{Theoretically and computationally convenient geometries on full-rank correlation matrices}},
    AUTHOR = {Thanwerdas, Yann and Pennec, Xavier},
    url-hal= {https://hal.archives-ouvertes.fr/hal-03527072},
    NOTE = {working paper or preprint},
    YEAR = {2022},
    MONTH = Jan,
    KEYWORDS = {SPD matrices ; Correlation matrices ; Lie group ; Lie group actions ; Quotient-affine metric ; Lie-Cholesky metrics ; Poly-hyperbolic-Cholesky metrics ; Euclidean-Cholesky metrics ; Log-Euclidean-Cholesky metrics ; 15B48 ; 15B99 ; 53-08 ; 53B21 ; 15A63 ; 53C22 ; 62H20 ; 58D17},
    PDF = {https://hal.archives-ouvertes.fr/hal-03527072/file/main.pdf},
    HAL_ID = {hal-03527072},
    HAL_VERSION = {v1},
    
    }
    



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