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Publications of Benoît Audelan

Thesis

  1. Benoît Audelan. Probabilistic segmentation modelling and deep learning-based lung cancer screening. Theses, Université Côte d'Azur, July 2021. Keyword(s): Medical imaging, Image segmentation, Artificial intelligence, Machine learning, Deep learning, Lung cancer, Imagerie médicale, Segmentation d'images, Intelligence artificielle, Apprentissage artificiel, Apprentissage profond, Cancer du poumon. [bibtex-entry]


Articles in journal, book chapters

  1. 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. [bibtex-entry]


  2. Benoît Audelan and Hervé Delingette. Unsupervised quality control of segmentations based on a smoothness and intensity probabilistic model. Medical Image Analysis, 68:101895, November 2020. Keyword(s): Unsupervised quality control, Image segmentation, Bayesian learning, Unsupervised quality control. [bibtex-entry]


  3. Simon Heeke, Jonathan Benzaquen, Elodie Long-Mira, Benoît Audelan, Virginie Lespinet, Olivier Bordone, Salomé Lalvée, Katia Zahaf, Michel Poudenx, Olivier Humbert, Henri Montaudié, Pierre-Michel Dugourd, Madleen Chassang, Thierry Passeron, Hervé Delingette, Charles-Hugo Marquette, Véronique Hofman, Albrecht Stenzinger, Marius Ilié, and Paul Hofman. In-House Implementation of Tumor Mutational Burden Testing to Predict Durable Clinical Benefit in Non-Small Cell Lung Cancer and Melanoma Patients. Cancers, 11, 2019. Keyword(s): tumor mutational burden, FoundationOne assay, Oncomine TML assay, lung cancer, melanoma, immunotherapy. [bibtex-entry]


Conference articles

  1. Benoît Audelan, Lopez Stéphanie, Pierre Fillard, yann Diascorn, Bernard Padovani, and Hervé Delingette. Validation of lung nodule detection a year before diagnosis in NLST dataset based on a deep learning system. In ERS 2021 - European Respiratory Society International Congress, Virtual, United Kingdom, September 2021. [bibtex-entry]


  2. Benoît Audelan, Dimitri Hamzaoui, Sarah Montagne, Raphaële Renard-Penna, and Hervé Delingette. Robust Fusion of Probability Maps. In MICCAI 2020 - 23rd International Conference on Medical Image Computing and Computer Assisted Intervention, Lima/ Virtuel, Peru, October 2020. [bibtex-entry]


  3. Benoît Audelan and Hervé Delingette. Unsupervised Quality Control of Image Segmentation based on Bayesian Learning. In MICCAI 2019 - 22nd International Conference on Medical Image Computing and Computer Assisted Intervention, Shenzhen, China, October 2019. Keyword(s): Image segmentation, Bayesian learning, Quality control. [bibtex-entry]



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Last modified: Sun Jul 3 00:30:10 2022
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