Valentin Oreiller

According to our database, Valentin Oreiller authored at least 17 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

A Bispectral 3D U-Net for Rotation Robustness in Medical Segmentation.

Arthur Chevalley, Valentin Oreiller, Julien Fageot, John O. Prior, Vincent Andrearczyk, Adrien Depeursinge

Proceedings of the Topology- and Graph-Informed Imaging Informatics, 2024

2023

Automatic Head and Neck Tumor segmentation and outcome prediction relying on FDG-PET/CT images: Findings from the second edition of the HECKTOR challenge.

Vincent Andrearczyk, Valentin Oreiller, Sarah Boughdad, Catherine Cheze Le Rest, Olena Tankyevych, Hesham Elhalawani, Mario Jreige, John O. Prior, Martin Vallières, Dimitris Visvikis, Mathieu Hatt, Adrien Depeursinge

Medical Image Anal., December, 2023

Why is the winner the best?

Matthias Eisenmann, Annika Reinke, Vivienn Weru, Minu Dietlinde Tizabi, Fabian Isensee, Tim J. Adler, Sharib Ali, Vincent Andrearczyk, Marc Aubreville, Ujjwal Baid, Spyridon Bakas, Niranjan Balu, Sophia Bano, Jorge Bernal, Sebastian Bodenstedt, Alessandro Casella, Veronika Cheplygina, Marie Daum, Marleen de Bruijne, Adrien Depeursinge, Reuben Dorent, Jan Egger, David G. Ellis, Sandy Engelhardt, Melanie Ganz, Noha M. Ghatwary, Gabriel Girard, Patrick Godau, Anubha Gupta, Lasse Hansen, Kanako Harada, Mattias P. Heinrich, Nicholas Heller, Alessa Hering, Arnaud Huaulmé, Pierre Jannin, Ali Emre Kavur, Oldrich Kodym, Michal Kozubek, Jianning Li, Hongwei Bran Li, Jun Ma, Carlos Martín-Isla, Bjoern H. Menze, J. Alison Noble, Valentin Oreiller, Nicolas Padoy, Sarthak Pati, Kelly Payette, Tim Rädsch, et al.

CoRR, 2023

Why is the Winner the Best?

Matthias Eisenmann, Annika Reinke, Vivienn Weru, Minu Dietlinde Tizabi, Fabian Isensee, Tim J. Adler, Sharib Ali, Vincent Andrearczyk, Marc Aubreville, Ujjwal Baid, Spyridon Bakas, Niranjan Balu, Sophia Bano, Jorge Bernal, Sebastian Bodenstedt, Alessandro Casella, Veronika Cheplygina, Marie Daum, Marleen de Bruijne, Adrien Depeursinge, Reuben Dorent, Jan Egger, David G. Ellis, Sandy Engelhardt, Melanie Ganz, Noha M. Ghatwary, Gabriel Girard, Patrick Godau, Anubha Gupta, Lasse Hansen, Kanako Harada, Mattias P. Heinrich, Nicholas Heller, Alessa Hering, Arnaud Huaulmé, Pierre Jannin, A. Emre Kavur, Oldrich Kodym, Michal Kozubek, Jianning Li, Hongwei Bran Li, Jun Ma, Carlos Martín-Isla, Bjoern H. Menze, J. Alison Noble, Valentin Oreiller, Nicolas Padoy, Sarthak Pati, Kelly Payette, Tim Rädsch, Jonathan Rafael-Patino, Vivek Singh Bawa, Stefanie Speidel, Carole H. Sudre, Kimberlin M. H. van Wijnen, Martin Wagner, D. Wei, Amine Yamlahi, Moi Hoon Yap, C. Yuan, Maximilian Zenk, A. Zia, David Zimmerer, Dogu Baran Aydogan, Binod Bhattarai, Louise Bloch, Raphael Brüngel, J. Cho, C. Choi, Q. Dou, Ivan Ezhov, Christoph M. Friedrich, C. Fuller, Rebati Raman Gaire, Adrian Galdran, Álvaro García-Faura, Maria Grammatikopoulou, S. Hong, Mostafa Jahanifar, I. Jang, Abdolrahim Kadkhodamohammadi, I. Kang, Florian Kofler, S. Kondo, Hugo Jaco Kuijf, M. Li, M. Luu, Tomaz Martincic, Pedro Morais, Mohamed A. Naser, Bruno Oliveira, David Owen, S. Pang, J. Park, S. Park, Szymon Plotka, Élodie Puybareau, Nasir M. Rajpoot, K. Ryu, Numan Saeed, Adam Shephard, Pengcheng Shi, Dejan Stepec, Ronast Subedi, Guillaume Tochon, Helena R. Torres, Hélène Urien, João L. Vilaça, Kareem A. Wahid, H. Wang, J. Wang, L. Wang, X. Wang, Benedikt Wiestler, Marek Wodzinski, F. Xia, J. Xie, Z. Xiong, Sen Yang, Y. Yang, Z. Zhao, Klaus H. Maier-Hein, Paul F. Jäger, Annette Kopp-Schneider, Lena Maier-Hein

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Head and neck tumor segmentation in PET/CT: The HECKTOR challenge.

Valentin Oreiller, Vincent Andrearczyk, Mario Jreige, Sarah Boughdad, Hesham Elhalawani, Joël Castelli, Martin Vallières, Simeng Zhu, Juanying Xie, Ying Peng, Andrei Iantsen, Mathieu Hatt, Yading Yuan, Jun Ma, Xiaoping Yang, Chinmay Rao, Suraj Pai, Kanchan Ghimire, Xue Feng, Mohamed A. Naser, Clifton D. Fuller, Fereshteh Yousefirizi, Arman Rahmim, Huai Chen, Lisheng Wang, John O. Prior, Adrien Depeursinge

Medical Image Anal., 2022

Robust Multi-Organ Nucleus Segmentation Using a Locally Rotation Invariant Bispectral U-Net.

Valentin Oreiller, Julien Fageot, Vincent Andrearczyk, John O. Prior, Adrien Depeursinge

Proceedings of the International Conference on Medical Imaging with Deep Learning, 2022

Overview of the HECKTOR Challenge at MICCAI 2022: Automatic Head and Neck Tumor Segmentation and Outcome Prediction in PET/CT.

Vincent Andrearczyk, Valentin Oreiller, Moamen Abobakr, Azadeh Akhavanallaf, Panagiotis Balermpas, Sarah Boughdad, Leo Capriotti, Joël Castelli, Catherine Cheze Le Rest, Pierre Decazes, Ricardo Correia, Dina El-Habashy, Hesham Elhalawani, Clifton D. Fuller, Mario Jreige, Yomna Khamis, Agustina La Greca Saint-Esteven, Abdallah Sherif Radwan Mohamed, Mohamed A. Naser, John O. Prior, Su Ruan, Stephanie Tanadini-Lang, Olena Tankyevych, Yazdan Salimi, Martin Vallières, Pierre Vera, Dimitris Visvikis, Kareem A. Wahid, Habib Zaidi, Mathieu Hatt, Adrien Depeursinge

Proceedings of the Head and Neck Tumor Segmentation and Outcome Prediction, 2022

Segmentation and Classification of Head and Neck Nodal Metastases and Primary Tumors in PET/CT.

Vincent Andrearczyk, Valentin Oreiller, Mario Jreige, Joël Castelli, John O. Prior, Adrien Depeursinge

Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

2021

Fully Automatic Head and Neck Cancer Prognosis Prediction in PET/CT.

Pierre Fontaine, Vincent Andrearczyk, Valentin Oreiller, Joël Castelli, Mario Jreige, John O. Prior, Adrien Depeursinge

Proceedings of the Multimodal Learning for Clinical Decision Support, 2021

Overview of the HECKTOR Challenge at MICCAI 2021: Automatic Head and Neck Tumor Segmentation and Outcome Prediction in PET/CT Images.

Vincent Andrearczyk, Valentin Oreiller, Sarah Boughdad, Catherine Cheze Le Rest, Hesham Elhalawani, Mario Jreige, John O. Prior, Martin Vallières, Dimitris Visvikis, Mathieu Hatt, Adrien Depeursinge

Proceedings of the Head and Neck Tumor Segmentation and Outcome Prediction, 2021

Multi-task Deep Segmentation and Radiomics for Automatic Prognosis in Head and Neck Cancer.

Vincent Andrearczyk, Pierre Fontaine, Valentin Oreiller, Joël Castelli, Mario Jreige, John O. Prior, Adrien Depeursinge

Proceedings of the Predictive Intelligence in Medicine - 4th International Workshop, 2021

Comparison of MR Preprocessing Strategies and Sequences for Radiomics-Based MGMT Prediction.

Daniel Abler, Vincent Andrearczyk, Valentin Oreiller, Javier Barranco Garcia, Diem Vuong, Stephanie Tanadini-Lang, Matthias Guckenberger, Mauricio Reyes, Adrien Depeursinge

Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2021

2020

Local rotation invariance in 3D CNNs.

Vincent Andrearczyk, Julien Fageot, Valentin Oreiller, Xavier Montet, Adrien Depeursinge

Medical Image Anal., 2020

3D Solid Spherical Bispectrum CNNs for Biomedical Texture Analysis.

Valentin Oreiller, Vincent Andrearczyk, Julien Fageot, John O. Prior, Adrien Depeursinge

CoRR, 2020

Automatic Segmentation of Head and Neck Tumors and Nodal Metastases in PET-CT scans.

Vincent Andrearczyk, Valentin Oreiller, Martin Vallières, Joël Castelli, Hesham Elhalawani, Mario Jreige, Sarah Boughdad, John O. Prior, Adrien Depeursinge

Proceedings of the International Conference on Medical Imaging with Deep Learning, 2020

Overview of the HECKTOR Challenge at MICCAI 2020: Automatic Head and Neck Tumor Segmentation in PET/CT.

Vincent Andrearczyk, Valentin Oreiller, Mario Jreige, Martin Vallières, Joël Castelli, Hesham Elhalawani, Sarah Boughdad, John O. Prior, Adrien Depeursinge

Proceedings of the Head and Neck Tumor Segmentation - First Challenge, 2020

2019

Exploring local rotation invariance in 3D CNNs with steerable filters.

Vincent Andrearczyk, Julien Fageot, Valentin Oreiller, Xavier Montet, Adrien Depeursinge

Proceedings of the International Conference on Medical Imaging with Deep Learning, 2019