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Validation of lung nodule detection a year before diagnosis in NLST dataset based on a deep learning system

Benoît Audelan , Lopez Stéphanie , Pierre Fillard , Yann Diascorn , Bernard Padovani , et al.
ERS 2021 - European Respiratory Society International Congress, Sep 2021, Virtual, United Kingdom. ⟨10.1183/13993003.congress-2021.OA4317⟩
Conference papers hal-03538729v1
Image document

In-House Implementation of Tumor Mutational Burden Testing to Predict Durable Clinical Benefit in Non-Small Cell Lung Cancer and Melanoma Patients

Simon Heeke , Jonathan Benzaquen , Elodie Long-Mira , Benoît Audelan , Virginie Lespinet , et al.
Journal articles hal-02381188v1
Image document

Robust Bayesian fusion of continuous segmentation maps

Benoît Audelan , Dimitri Hamzaoui , Sarah Montagne , Raphaële Renard-Penna , Hervé Delingette
Medical Image Analysis, 2022, 78, pp.102398. ⟨10.1016/⟩
Journal articles hal-03594219v1
Image document

Unsupervised quality control of segmentations based on a smoothness and intensity probabilistic model

Benoît Audelan , Hervé Delingette
Medical Image Analysis, 2020, 68, pp.101895. ⟨10.1016/⟩
Journal articles hal-03044140v1
Image document

Unsupervised Quality Control of Image Segmentation based on Bayesian Learning

Benoît Audelan , Hervé Delingette
MICCAI 2019 - 22nd International Conference on Medical Image Computing and Computer Assisted Intervention, Oct 2019, Shenzhen, China
Conference papers hal-02265131v1
Image document

Probabilistic segmentation modelling and deep learning-based lung cancer screening

Benoît Audelan
Image Processing [eess.IV]. Université Côte d'Azur, 2021. English. ⟨NNT : 2021COAZ4054⟩
Theses tel-03406789v1