Sheet of MERIAUDEAU Fabrice

• Fev 2024/..:  Conseiller Scientifique HCERES, ST6
• Fev 2023/.. :  Conseiller DGESIP
• Oct 2018: Professeur CE2 des Universités, IUT du Creusot.
• 2016/2018 : Professeur – Universiti Teknologi PETRONAS (Malaisie)
• Sept 2014:  Professeur CE1 des Universités, IUT du Creusot.
• Sept 2008 : Professeur 1C des Universités, IUT du Creusot.
• Sept 2004 : Professeur 2C des Universités, IUT du Creusot.
• Déc 2002 : Habilitation à Diriger les Recherches.
• Sept 1998 : Maître de conférences, IUT du Creusot.
• 1997/1998 : Postdoctorant Laboratoire National d’Oak Ridge (USA).
• Mai 1997: Doctorat de l’Université de Bourgogne (FJ), Dijon.
• Nov 1994 : Diplôme d’Ingénieurs (FIRST), spécialisation : matériaux, (Dijon).
• Juin 1994: DEA de Physique (Dijon), mention Bien.

• Fev 2024/..:  Conseiller Scientifique HCERES, ST6
• Fev 2023/.. :  Conseiller DGESIP
• Oct 2018: Professeur CE2 des Universités, IUT du Creusot.
• 2016/2018 : Professeur – Universiti Teknologi PETRONAS (Malaisie)
• Sept 2014:  Professeur CE1 des Universités, IUT du Creusot.
• Sept 2008 : Professeur 1C des Universités, IUT du Creusot.
• Sept 2004 : Professeur 2C des Universités, IUT du Creusot.
• Déc 2002 : Habilitation à Diriger les Recherches.
• Sept 1998 : Maître de conférences, IUT du Creusot.
• 1997/1998 : Postdoctorant Laboratoire National d’Oak Ridge (USA).
• Mai 1997: Doctorat de l’Université de Bourgogne (FJ), Dijon.
• Nov 1994 : Diplôme d’Ingénieurs (FIRST), spécialisation : matériaux, (Dijon).
• Juin 1994: DEA de Physique (Dijon), mention Bien.

• 2021/2024 France Relance coordonné, coordinateur de deux projets industriels avec la société APEIRA (montant total de 240 k€).
• 2022/2024 Coordinateur projet Region UBFC, Graduate School INTHERAPI. (60k€)
• 2022/.. Porteur local de l’ANR PRC Mediseg Home – mediseg (litislab.fr), débuté en Janvier 2022. (85 k€)

Publications

1. Samiksha Pachade, Prasanna Porwal, Manesh Kokare, Girish Deshmukh, Vivek Sahasrabuddhe, Zhengbo Luo, Feng Han, Zitang Sun, Li Qihan, Sei-ichiro Kamata, Edward Ho, Edward Wang, Asaanth Sivajohan, Saerom Youn, Kevin Lane, Jin Chun, Xinliang Wang, Yunchao Gu, Sixu Lu, Young-tack Oh, Hyunjin Park, Chia-Yen Lee, Hung Yeh, Kai-Wen Cheng, Haoyu Wang, Jin Ye, Junjun He, Lixu Gu, Dominik Müller, Iñaki Soto-Rey, Frank Kramer, Hidehisa Arai, Yuma Ochi, Takami Okada, Luca Giancardo, Gwenolé Quellec, Fabrice Mériaudeau,
   RFMiD: Retinal Image Analysis for multi-Disease Detection challenge,
   Medical Image Analysis, Volume 99, 2025, 103365, ISSN 1361-8415, https://doi.org/10.1016/j.media.2024.103365.
2. Quinton, F., Presles, B., Leclerc, S. et al. Navigating the nuances: comparative analysis and hyperparameter optimisation of neural architectures on contrast-enhanced MRI for liver and liver tumour segmentation. Sci Rep 14, 3522 (2024). https://doi.org/10.1038/s41598-024-53528-9
3. Tewodros Weldebirhan Arega, Stéphanie Bricq, François Legrand, Alexis Jacquier, Alain Lalande, Fabrice Meriaudeau, « Automatic uncertainty-based quality controlled T1 mapping and ECV analysis from native and post-contrast cardiac T1 mapping images using Bayesian vision transformer » Medical Image Analysis (Q1), Volume 86, 2023, 102773, ISSN 1361-8415, https://doi.org/10.1016/j.media.2023.102773.
4. Alain Lalande, Zhihao Chen, Thibaut Pommier, Thomas Decourselle, Abdul Qayyum, Michel Salomon, Dominique Ginhac, Youssef Skandarani, Arnaud Boucher, Khawla Brahim, Marleen de Bruijne, Robin Camarasa, Teresa M. Correia, Xue Feng, Kibrom B. Girum, Anja Hennemuth, Markus Huellebrand, Raabid Hussain, Matthias Ivantsits, Jun Ma, Craig Meyer, Rishabh Sharma, Jixi Shi, Nikolaos V. Tsekos, Marta Varela, Xiyue Wang, Sen Yang, Hannu Zhang, Yichi Zhang, Yuncheng Zhou, Xiahai Zhuang, Raphael Couturier, Fabrice Meriaudeau, »Deep learning methods for automatic evaluation of delayed enhancement-MRI. The results of the EMIDEC challenge », Medical Image Analysis (Q1), Volume 79, 2022, 102428, ISSN 1361-8415, https://doi.org/10.1016/j.media.2022.102428.
5. Wu, G. Allibert, F. Meriaudeau, C. Ma and C. Demonceaux, “HiDAnet: RGB-D Salient Object Detection via Hierarchical Depth Awareness,” in IEEE Transactions on Image Processing (Q1), vol. 32, pp. 2160-2173, 2023, doi: 10.1109/TIP.2023.3263111.
6. Samiksha Pachade, Prasanna Porwal, Manesh Kokare, Luca Giancardo, Fabrice Mériaudeau, NENet: Nested EfficientNet and adversarial learning for joint optic disc and cup segmentation, Medical Image Analysis (Q1), Volume 74, 2021, 102253, ISSN 1361-8415, https://doi.org/10.1016/j.media.2021.102253.
7. Abdul Qayyum, Alain Lalande, Fabrice Meriaudeau, Automatic segmentation of tumors and affected organs in the abdomen using a 3D hybrid model for computed tomography imaging, Computers in Biology and Medicine (Q1), Volume 127,2020, 104097, ISSN 0010-4825, https://doi.org/10.1016/j.compbiomed.2020.104097.
8. Alsaih, M.Z. Yusoff, T.B. Tang, I. Faye, F. Mériaudeau, Deep learning architectures analysis for age-related macular degeneration segmentation on optical coherence tomography scans, Computer Methods and Programs in Biomedicine (Q1), Volume 195, 2020, 105566, ISSN 0169-2607, https://doi.org/10.1016/j.cmpb.2020.105566.

Communications

1. Anneke Annassia Putri Siswadi, Stéphanie Bricq, and Fabrice Meriaudeau “Multi-label ocular abnormalities detection with semantic dictionary learning”, Proc. SPIE 12465, Medical Imaging 2023: Computer-Aided Diagnosis, 1246513 (7 April 2023); https://doi.org/10.1117/12.2653834.
2. Syed Nouman Hasany, Caroline Petitjean, Fabrice Mériaudeau; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2023, pp. 3733-3738 (spotlight paper)
3. Qayyum, A., Mazher, M., Niederer, S., Meriaudeau, F., Razzak, I. (2022). Automatic Cardiac Magnetic Resonance Respiratory Motions Assessment and Segmentation. In: Camara, O., et al. Statistical Atlases and Computational Models of the Heart. Regular and CMRxMotion Challenge Papers. STACOM 2022. Lecture Notes in Computer Science, vol 13593. Springer, Cham. https://doi.org/10.1007/978-3-031-23443-9_46
4.  Mahmoud Abdelhamed and Fabrice Meriaudeau “NesT UNet: pure transformer segmentation network with an application for automatic cardiac myocardial infarction evaluation”, Proc. SPIE 12465, Medical Imaging 2023: Computer-Aided Diagnosis, 124652L (7 April 2023); https://doi.org/10.1117/12.2654162
5.  Syed Nouman Hasany, Caroline Petitjean, and Fabrice Meriaudeau “A study of attention information from transformer layers in hybrid medical image segmentation networks”, Proc. SPIE 12464, Medical Imaging 2023: Image Processing, 124641O (3 April 2023); https://doi.org/10.1117/12.2652215.
6. Arega, T.W., Legrand, F., Bricq, S., Meriaudeau, F.: Using MRI-specific data augmentation to enhance the segmentation of right ventricle in multi-disease, multi-center and multi-view cardiac MRI. In: Puyol Antón, E., et al. (eds.) STACOM 2021. LNCS, vol. 13131, pp. 250–258. Springer, Cham (2022). https://doi.org/10.1007/978-3-030-93722-5_27
7. Arega, T.W., Bricq, S., Meriaudeau, F. (2023). Using Polynomial Loss and Uncertainty Information for Robust Left Atrial and Scar Quantification and Segmentation. In: Zhuang, X., Li, L., Wang, S., Wu, F. (eds) Left Atrial and Scar Quantification and Segmentation. LAScarQS 2022. Lecture Notes in Computer Science, vol 13586. Springer, Cham. https://doi.org/10.1007/978-3-031-31778-1_13
8. Anneke Putri Siswadi, S. Bricq and F. Meriaudeau, “Microaneurysms Detection in Color Fundus Image with Feature-based Background Suppression,” 2022 26th International Conference on Pattern Recognition (ICPR), Montreal, QC, Canada, 2022, pp. 4594-4600, doi: 10.1109/ICPR56361.2022.9956460.
9. Zhang, H. Wang, C. Li and F. Meriaudeau, “Complex-valued Deep Network aided Channel Tracking for Underwater Acoustic communications,” OCEANS 2022 – Chennai, Chennai, India, 2022, pp. 1-5, doi: 10.1109/OCEANSChennai45887.2022.9775455.
10. Arega, T.W., Legrand, F., Bricq, S., Meriaudeau, F. (2022). Using MRI-specific Data Augmentation to Enhance the Segmentation of Right Ventricle in Multi-disease, Multi-center and Multi-view Cardiac MRI. In: Puyol Antón, E., et al. Statistical Atlases and Computational Models of the Heart. Multi-Disease, Multi-View, and Multi-Center Right Ventricular Segmentation in Cardiac MRI Challenge. STACOM 2021. Lecture Notes in Computer Science, vol 13131. Springer, Cham. https://doi.org/10.1007/978-3-030-93722-5_27