• 
  Voichiţa Maxim, Yuemeng Feng, Hussein Banjak, Elie Bretin. Tomographic reconstruction from Poisson distributed data: a fast and convergent EM-TV dual approach. Numerical Algorithms, 2023, 94, pp.701-731. ⟨10.1007/s11075-023-01517-w⟩. ⟨hal-04134998⟩
• 
  Rémy Gauthier, Biolang Yu, Cécile Olivier, Julie Villanova, Max Langer, et al.. Human femoral lacuno-canalicular network by X-ray nano-CT. 48e Congrès de la Société de Biomécanique, 48e Congrès de la Société de Biomécanique, Oct 2023, Grenoble (France), France. pp.S36-S37. ⟨hal-04289439⟩
• 
  Olivier Flasseur, Loïc Denis, Éric Thiébaut, Thomas Olivier, Corinne Fournier. ExPACO: detection of an extended pattern under nonstationary correlated noise by patch covariance modeling. EUSIPCO 2019, Sep 2019, Coruna, Spain. ⟨10.23919/EUSIPCO.2019.8903021⟩. ⟨hal-02308808⟩
• 
  Joseph Angelo, Vivek Venugopal, Frédéric Fantoni, Vincent Poher, Irving J. Bigio, et al.. Depth-enhanced fluorescence imaging using masked detection of structured illumination. Journal of Biomedical Optics, 2014, 19 (11), pp.116008. ⟨10.1117/1.JBO.19.11.116008⟩. ⟨hal-01131906⟩
• 
  Yamil Vindas, Blaise Kévin Guépié, Marilys Almar, Emmanuel Roux, Philippe Delachartre. Trainable pruned ternary quantization for medical signal classification models. Neurocomputing, 2024, pp.128216. ⟨10.1016/j.neucom.2024.128216⟩. ⟨hal-04652637v2⟩
• 
  Gabriele Belotti, Giovanni Fattori, Guido Baroni, Simon Rit. Extension of the cone‐beam CT field‐of‐view using two complementary short scans. Medical Physics, 2024, 51 (5), pp.3391-3404. ⟨10.1002/mp.16869⟩. ⟨hal-04320045v2⟩
• 
  Valentine Wargnier-Dauchelle, Thomas Grenier, Michaël Sdika. An unexpected confounder: how brain shape can be used to classify MRI scans ?. Medical Imaging with Deep Learning, Jul 2024, Paris, France. ⟨hal-04561863⟩
• 
  Valentine Wargnier-Dauchelle, Thomas Grenier, Françoise Durand-Dubief, François Cotton, Michaël Sdika. Constrained non-negative networks for a more explainable and interpretable classification. Medical Imaging with Deep Learning, Jul 2024, Paris, France. ⟨hal-04561860⟩
• 
  Thomas Maitre, Elie Bretin, Romain Phan, Nicolas Ducros, Michaël Sdika. Dynamic Single-Pixel Imaging on an Extended Field of View without Warping the Patterns. International Conference on Medical Image Computing and Computer Assisted Intervention, Oct 2024, Marrakech, Morocco. ⟨hal-04533981v1⟩
• 
  Julia Puig, Denis Friboulet, Hang Jung Ling, François Varray, Jonathan Porée, et al.. Boosting Cardiac Color Doppler Frame Rates with Deep Learning. 2024. ⟨hal-04495325⟩
• 
  Andrew King, Nicolas Duchateau. Conclusions. AI and Big Data in Cardiology, Springer International Publishing, pp.201-203, 2023, ⟨10.1007/978-3-031-05071-8_11⟩. ⟨hal-04212071⟩
• 
  Nicolas Duchateau, Oscar Camara, Rafael Sebastian, Andrew King. Analysis of Non-imaging Data. AI and Big Data in Cardiology, Springer International Publishing, pp.183-200, 2023, ⟨10.1007/978-3-031-05071-8_10⟩. ⟨hal-04212070⟩
• 
  Buntheng Ly, Mihaela Pop, Hubert Cochet, Nicolas Duchateau, Declan O’regan, et al.. Outcome Prediction. AI and Big Data in Cardiology : A Practical Guide, Springer International Publishing, pp.105-133, 2023, 978-3-031-05070-1. ⟨10.1007/978-3-031-05071-8_6⟩. ⟨hal-04212068⟩
• 
  Daniel Rueckert, Moritz Knolle, Nicolas Duchateau, Reza Razavi, Georgios Kaissis. Diagnosis. AI and Big Data in Cardiology, Springer International Publishing, pp.85-103, 2023, ⟨10.1007/978-3-031-05071-8_5⟩. ⟨hal-04212059⟩
• 
  Pierre-Marc Jodoin, Nicolas Duchateau, Christian Desrosiers. From Machine Learning to Deep Learning. AI and Big Data in Cardiology, Springer International Publishing, pp.35-56, 2023, ⟨10.1007/978-3-031-05071-8_3⟩. ⟨hal-04212050⟩
• 
  Nicolas Duchateau, Esther Puyol-Antón, Bram Ruijsink, Andrew King. AI and Machine Learning: The Basics. AI and Big Data in Cardiology, Springer International Publishing, pp.11-33, 2023, ⟨10.1007/978-3-031-05071-8_2⟩. ⟨hal-04212045⟩
• 
  Andrew King, Nicolas Duchateau. Introduction. AI and Big Data in Cardiology, Springer International Publishing, pp.1-10, 2023, ⟨10.1007/978-3-031-05071-8_1⟩. ⟨hal-04212037⟩
• 
  Nicolas Duchateau, Oscar Camara. Machine learning and biophysical models: how to benefit each other?. Reduced Order Models for the Biomechanics of Living Organs, Elsevier, pp.147-164, 2023, ⟨10.1016/B978-0-32-389967-3.00009-3⟩. ⟨hal-04212035⟩
• 
  Laurent Bitker, Nadja Cristinne Carvalho, Sascha Reidt, Christoph Schranz, Dominik Novotni, et al.. Validation of a novel system to assess end-expiratory lung volume and alveolar recruitment in an ARDS model. Intensive Care Medicine Experimental, 2021, 9 (1), pp.46. ⟨10.1186/s40635-021-00410-x⟩. ⟨hal-03688174⟩
• 
  Bin Gao, Wanyu Liu, Liang Wang, Zhengjun Liu, Pierre Croisille, et al.. Estimation of cardiac motion in cine-MRI sequences by correlation transform optical flow of monogenic features distance. Physics in Medicine and Biology, 2016, 61 (24), pp.8640. ⟨10.1088/1361-6560/61/24/8640⟩. ⟨hal-01434871⟩

358

538