Vincent Andrearczyk - HES SO Valais Publications

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First name(s):	Vincent
Last name(s):	Andrearczyk
Institute:	II

| 1-50 | 51-96 |

Daniel Abler, Vincent Andrearczyk, Valentin Oreiller, Javier Barranco Garcia, Diem Vuong, Stephanie Tanadini-Lang, Matthias Guckenberger, Mauricio Reyes and Adrien Depeursinge, Comparison of MR preprocessing strategies and sequences for radiomics-based MGMT prediction, in: Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries (MICCAI/BrainLes 2021), Cham, pages 367–380, Springer International Publishing, 2022

[DOI]

Kudaibergen Abutalip, Numan Saeed, Fadillah Maani, Ikboljon Sobirov, Vincent Andrearczyk, Adrien Depeursinge and Mohammad Yaqub, LEXU: Learning from Expert Disagreement for Single-Pass Uncertainty Estimation in Medical Image Segmentation, in: International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, 2025

Mohammadreza Amirian, Arthur Chevalley, Vincent Andrearczyk, Ran Klein, Robert DeKemp, Eric Moulton, Christel H. Kamani, John O. Prior, Mario Jreige and Adrien Depeursinge, Left Ventricle Segmentation in Dynamic 82Rb PET/CT Using Deep Convolutional Neural Networks, 2025

Vincent Andrearczyk and Adrien Depeursinge, Rotational 3D Texture Classification Using Group Equivariant CNNs (2018), in: ArXiv

[URL]

Vincent Andrearczyk, Adrien Depeursinge and Henning Müller, Neural Network Training for Cross-Protocol Radiomic Feature Standardization in Computed Tomography (2019), in: Journal of Medical Imaging, 6:3(024008)

[URL]

Vincent Andrearczyk, Adrien Depeursinge and Henning Müller, Learning Cross-Protocol Radiomics and Deep Feature Standardization from CT Images of Texture Phantoms, in: SPIE Medical Imaging 2019, International Society for Optics and Photonics, pages 109-116, SPIE, 2019

Vincent Andrearczyk, Julien Fageot, Valentin Oreiller, Xavier Montet and Adrien Depeursinge, Local Rotation Invariance in 3D CNNs (2020), in: Medical Image Analysis, 65(101756)

[]: IF 2018 = 8.79

[DOI]
[URL]

Vincent Andrearczyk, Julien Fageot, Valentin Oreiller, Xavier Montet and Adrien Depeursinge, Exploring local rotation invariance in 3D CNNs with steerable filters, in: Medical Imaging with Deep Learning, pages 15-26, Proceedings of Machine Learning Research, 2019

[]: Won the overall best paper award of MIDL 2019 !

[URL]

Vincent Andrearczyk, Pierre Fontaine, Valentin Oreiller, Joel Castelli, Mario Jreige, John O. Prior and Adrien Depeursinge, Multi-Task Deep Segmentation and Radiomics for Automatic Prognosis in Head and Neck Cancer, in: 4th Workshop on PRedictive Intelligence in MEdicine, pages 147-156, Springer LNCS, 2021

[URL]

Vincent Andrearczyk, Mara Graziani, Henning Müller and Adrien Depeursinge, Consistency of Scale Covariance in Internal Representations of CNNs, in: Irish Machine Vision and Image Processing Conference, 2020

Vincent Andrearczyk and Henning Müller, Deep Multimodal Classification of Image Types in Biomedical Journal Figures, in: CLEF 2018, Avignon, France, Springer, 2018

Vincent Andrearczyk, Valentin Oreiller, Moamen Abobakr, Azadeh Akhavanallaf, Panagiotis Balermpas, Sarah Boughdad, Leo Capriotti, Joel Castelli, Catherine Cheze Le Rest, Pierre Decazes, Ricardo Correia, Dina El-Habashy, Hesham Elhalawani, Clifton D. Fuller, Mario Jreige, Yomna Khamis, Agustina La Greca, Abdallah Mohamed, Mohamed Naser, John O. Prior, Su Ruan, Stephanie Tanadini-Lang, Olena Tankyevych, Yazdan Salimi, Martin Vallìères, Pierre Vera, Dimitris Visvikis, Kareem Wahid, Habib Zaidi, Mathieu Hatt and Adrien Depeursinge, Overview of the HECKTOR Challenge at MICCAI 2022: Automatic Head and Neck Tumor Segmentation and Outcome Prediction in PET/CT, pages 1-30, Springer, Cham, 2023

[DOI]
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Vincent Andrearczyk, Valentin Oreiller, Sarah Boughdad, Catherine Cheze-Le-Rest, Hesham Elhalawani, Mario Jreige, John O. Prior, Martin Vallìères, Dimitris Visvikis, Mathieu Hatt and Adrien Depeursinge, Overview of the HECKTOR Challenge at MICCAI 2021: Automatic Head and Neck Tumor Segmentation and Outcome Prediction in PET/CT Images, in: Head and Neck Tumor Segmentation and Outcome Prediction, pages 1-37, 2022

[DOI]
[URL]

Vincent Andrearczyk, Valentin Oreiller, Sarah Boughdad, Catherine Cheze-Le-Rest, Olena Tankyevych, Hesham Elhalawani, Mario Jreige, John O. Prior, Martin Vallìères, Dimitris Visvikis, Mathieu Hatt and Adrien Depeursinge, Automatic Head and Neck Tumor Segmentation and Outcome Prediction Relying on FDG-PET/CT Images: Findings from the Second Edition of the HECKTOR Challenge (2023), in: Medical Image Analysis, 90:1(102972)

[]: IF 2022: 10.9

[URL]

Vincent Andrearczyk, Valentin Oreiller and Adrien Depeursinge, Wide kernels and their DCT compression in convolutional networks for nuclei segmentation (2023), in: Informatics in Medicine Unlocked, 43(101403)

[DOI]
[URL]

Head and Neck Tumor Segmentation, Springer International Publishing, 2021

[URL]

Vincent Andrearczyk, Valentin Oreiller and Adrien Depeursinge, Oropharynx Detection in PET-CT for Tumor Segmentation, in: Irish Machine Vision and Image Processing Conference, 2020, 2020

Vincent Andrearczyk, Valentin Oreiller, Julien Fageot, Xavier Montet and Adrien Depeursinge, Solid Spherical Energy (SSE) CNNs for Efficient 3D Medical Image Analysis, in: Irish Machine Vision and Image Processing Conference, pages 37-44, 2019

Vincent Andrearczyk, Valentin Oreiller, Mathieu Hatt and Adrien Depeursinge, Head and Neck Tumor Segmentation and Outcome Prediction, Springer International Publishing, 2023

[DOI]
[URL]

Head and Neck Tumor Segmentation and Outcome Prediction, Springer International Publishing, 2022

[DOI]
[URL]

Vincent Andrearczyk, Valentin Oreiller, Mario Jreige, Sarah Boughdad, Catherine Cheze-Le-Rest, John O. Prior, Mathieu Hatt and Adrien Depeursinge, HEad and neCK TumOR segmentation and outcome prediction using AI: lessons from three consecutive years of the HECKTOR challenge, in: European Head and Neck Society (EHNS) on Artificial Intelligence (AI) in Head & Neck Oncology, Lausanne and virtual, 2023

Vincent Andrearczyk, Valentin Oreiller, Mario Jreige, Joel Castelli, John O. Prior and Adrien Depeursinge, Segmentation and Classification of Head and Neck Nodal Metastases and Primary Tumors in PET/CT, in: 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), pages 4731-4735, 2022

Vincent Andrearczyk, Valentin Oreiller, Mario Jreige, Hesham Elhalawani, Sarah Boughdad, Catherine Cheze-Le-Rest, John O. Prior, Mathieu Hatt and Adrien Depeursinge, HEad and neCK TumOR segmentation and outcome prediction: The HECKTOR challenge, in: European Society of Radiology, 2022

Vincent Andrearczyk, Valentin Oreiller, Mario Jreige, Martin Vallìères, Hesham Elhalawani, Sarah Boughdad, John O. Prior and Adrien Depeursinge, Overview of the HECKTOR Challenge at MICCAI 2020: Automatic Head and Neck Tumor Segmentation in PET/CT, pages 1-21, 2021

Vincent Andrearczyk, Valentin Oreiller, Martin Vallìères, Joel Castelli, Hesham Elhalawani, Mario Jreige, Sarah Boughdad, John O. Prior and Adrien Depeursinge, Automatic Segmentation of Head and Neck Tumors and Nodal Metastases in PET-CT scans, in: Medical Imaging with Deep Learning, Montréal, Canada, 2020

[URL]

Vincent Andrearczyk, Luis Schiappacasse, Daniel Abler, Marek Wodzinski, Andreas Hottinger, Matthieu Raccaud, Jean Bourhis, John O. Prior, Vincent Dunet and Adrien Depeursinge, Automatic Detection and Multi-Component Segmentation of Brain Metastases in Longitudinal MRI (2024), in: Nature Scientic Reports, 14:1(1-10)

Vincent Andrearczyk, Luis Schiappacasse, Jean Bourhis, John O. Prior, Michel Cuendet, Andreas Hottinger, Vincent Dunet and Adrien Depeursinge, The value of AI for assessing longitudinal brain metastases treatment response (2025), in: Neuro-Oncology Advances, 7:1

[URL]

Shruti Atul Mali, Abdalla Ibrahim, Henry C. Woodruff, Vincent Andrearczyk, Henning Müller, Sergey Primakov, Zohaib Salahuddin, Avishek Chatterjee and Philippe Lambin, Making Radiomics More Reproducible across Scanner and Imaging Protocol Variations: A Review of Harmonization Methods (2021), in: Journal of Personalized Medicine, 11:9

[URL]

Shruti Atul Mali, Nastaran Mohammadian Rad, Henry C. Woodruff, Adrien Depeursinge, Vincent Andrearczyk and Philippe Lambin, Harmonizing CT scanner acquisition variability in an anthropomorphic phantom: A Comparative Study of Image-level and Feature-level Harmonization using GAN, ComBat, and their Combination (2025), in: Plos One

Sacha Bors, Daniel Abler, Matthieu Dietz, Vincent Andrearczyk, Julien Fageot, Marie Nicod-Lalonde, Niklaus Schaefer, Robert DeKemp, Christel H. Kamani, John O. Prior and Adrien Depeursinge, Comparing various AI approaches to traditional quantitative assessment of the myocardial perfusion in [82Rb] PET for MACE prediction (2024), in: Nature Scientific Reports, 14:9644

[DOI]

Arthur Chevalley, Guillaume Bonnet, Mohammadreza Amirian, Vincent Andrearczyk, Sacha Bors, Ran Klein, Robert DeKemp, Eric Moulton, John O. Prior, Mario Jreige, Christel H. Kamani and Adrien Depeursinge, AI-based Prediction of Myocardium Viability Using [82Rb] PET/CT, 2025

Arthur Chevalley, Valentin Oreiller, Julien Fageot, John O. Prior, Vincent Andrearczyk and Adrien Depeursinge, A Bispectral 3D UNet for Rotation Robustness in Medical Segmentation, in: The First Workshop on Topology- and Graph-Informed Imaging Informatics at MICCAI, pages 43-54, Springer Nature Switzerland, 2024

[DOI]
[URL]

Victor H. Contreras, Andrea Bagante, Niccolò Marini, Michael Schumacher, Vincent Andrearczyk and Davide Calvaresi, Explanation Generation via Decompositional Rules Extraction for Head and Neck Cancer Classification, in: Explainable and Transparent AI and Multi-Agent Systems, 2023

Adrien Depeursinge, Vincent Andrearczyk, Philip Whybra, Joost van Griethuysen, Henning Müller, Roger Schaer, Martin Vallìères and Alex Zwanenburg, Standardised convolutional filtering for radiomics, 2020

[URL]

Adrien Depeursinge, Julien Fageot, Vincent Andrearczyk, John-Paul Ward and Michael Unser, Rotation Invariance and Directional Sensitivity: Spherical Harmonics versus Radiomics Features, in: Machine Learning in Medical Imaging (MLMI), pages 107--115, Springer International Publishing, 2018

[URL]

Anjani Dhrangadhariya, Oscar Jimenez del Toro, Vincent Andrearczyk, Manfredo Atzori and Henning Müller, Exploiting the PubMed Central repository to mine out a large multimodal dataset of rare cancer studies, in: SPIE Medical Imaging, Houston, TX, USA, 2020

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 Ghatwary, Gabriel Girard, Patrick Godau, Anubha Gupta, Lasse Hansen, Kanako Harada, Mattias Heinrich, Nicholas Heller, Alessa Hering, Arnaud Huaulmé, Pierre Jannin, Ali Emre Kavur, Oldřich Kodym, Michal Kozubek, Jianning Li, Hongwei Li, Jun Ma, Carlos Martín-Isla, Bjoern Menze, Alison Noble, Valentin Oreiller, Nicolas Padoy, Sarthak Pati, Kelly Payette, Tim Rätsch, Jonathan Rafael-Patiño, Vivek Singh Bawa, Stefanie Speidel, Carole H Sudre, Kimberlin van Wijnen, Martin Wagner, Donglai Wei, Amine Yamlahi, Moi Hoon Yap, Chun Yuan, Maximilian Zenk, Aneeq Zia, David Zimmerer, Dogu Baran Aydogan, Binod Bhattarai, Louise Bloch, Raphael Brüngel, Jihoon Cho, Chanyeol Choi, Qi Dou, Ivan Ezhov, Christoph M. Friedrich, Clifton Fuller, Rebati Raman Gaire, Adrian Galdran, Álvaro García Faura, Maria Grammatikopoulou, SeulGi Hong, Mostafa Jahanifar, Ikbeom Jang, Abdolrahim Kadkhodamohammadi, Inha Kang, Florian Kofler, Satoshi Kondo, Hugo Kuijf, Mingxing Li, Minh Huan Luu, Tomaž Martinčič, Pedro Morais, Mohamed A. Naser, Bruno Oliveira, David Owen, Subeen Pang, Jinah Park, Sung-Hong Park, Szymon Plotka, Elodie Puybareau, Nasir Rajpoot, Kanghyun Ryu, Numan Saeed, Adam Shephard, Pengcheng Shi, Dejan Štepec, Ronast Subedi, Guillaume Tochon, Helena R. Torres, Helene Urien, João L. Vilaça, Kareem Abdul Wahid, Haojie Wang, Jiacheng Wang, Liansheng Wang, Xiyue Wang, Benedikt Wiestler, Marek Wodzinski, Fangfang Xia, Juanying Xie, Zhiwei Xiong, Sen Yang, Yanwu Yang, Zixuan Zhao, Klaus Maier-Hain, Paul F. Jäger, Annette Kopp-Schneider and Lena Maier-Hein, Why is the winner the best?, in: CVPR, 2023

[URL]

Matthias Eisenmann, Annika Reinke, Vivienn Weru, Minu Dietlinde Tizabi, Fabian Isensee, Tim J. Adler, Patrick Godau, Veronika Cheplygina, Michal Kozubek, Sharib Ali, Anubha Gupta, Jan Kybic, Alison Noble, Carlos Ortiz de Solórzano, Samiksha Pachade, Caroline Petitjean, Daniel Sage, Donglai Wei, Elizabeth Wilden, Deepak Alapatt, Vincent Andrearczyk, Ujjwal Baid, Spyridon Bakas, Niranjan Balu, Sophia Bano, Vivek Singh Bawa, Jorge Bernal, Sebastian Bodenstedt, Alessandro Casella, Jinwook Choi, Olivier Commowick, Marie Daum, Adrien Depeursinge, Reuben Dorent, Jan Egger, Hannah Eichhorn, Sandy Engelhardt, Melanie Ganz, Gabriel Girard, Lasse Hansen, Mattias Heinrich, Nicholas Heller, Alessa Hering, Arnaud Huaulmé, Hyunjeong Kim, Bennett A Landman, Hongwei Bran Li, Jianning Li, Jun Ma, Anne Martel, Carlos Martín-Isla, Bjoern Menze, Chinedu Innocent Nwoye, Valentin Oreiller, Nicolas Padoy, Sarthak Pati, Kelly Payette, Carole H Sudre, Kimberlin van Wijnen, Armine Vardazaryan, Tom Vercauteren, Martin Wagner, Chuanbo Wang, Moi Hoon Yap, Zeyun Yu, Chun Yuan, Maximilian Zenk, Aneeq Zia, David Zimmerer, Rina Bao, Chanyeol Choi, Andrew Cohen, Oleh Dzyubachyk, Adrian Galdran, Tianyuan Gan, Tianqi Guo, Pradyumna Gupta, Mahmood Haithami, Edward Ho, Ikbeom Jang, Zhili Li, Zhengbo Luo, Filip Lux, Sokratis Makrogiannis, Dominik Müller, Young-tack Oh, Subeen Pang, Constantin Pape, Gorkem Polat, Charlotte Rosalie Reed, Kanghyun Ryu, Tim Scherr, Vajira Thambawita, Haoyu Wang, Xinliang Wang, Kele Xu, Hung Yeh, Doyeob Yeo, Yixuan Yuan, Yan Zeng, Xin Zhao, Julian Abbing, Jannes Adam, Nagesh Adluru, Niklas Agethen, Salman Ahmed, Yasmina Al Khalil, Mireia Alenyà, Esa Alhoniemi, Chengyang An, Talha Anwar, Tewodros Weldebirhan Arega, Netanell Avisdris, Dogu Baran Aydogan, Yingbin Bai, Maria Baldeon Calisto, Berke Doga Basaran, Marcel Beetz, Cheng Bian, Hao Bian, Kevin Blansit, Louise Bloch, Robert Bohnsack, Sara Bosticardo, Jack Breen, Mikael Brudfors, Raphael Brüngel, Mariano Cabezas, Alberto Cacciola, Zhiwei Chen, Yucong Chen, Daniel Tianming Chen, Minjeong Cho, Min-Kook Choi, Chuantao Xie Chuantao Xie, Dana Cobzas, Julien Cohen-Adad, Jorge Corral Acero, Sujit Kumar Das, Marcela de Oliveira, Hanqiu Deng, Guiming Dong, Lars Doorenbos, Cory Efird, Di Fan, Mehdi Fatan Serj, Alexandre Fenneteau, Lucas Fidon, Patryk Filipiak, René Finzel, Nuno R. Freitas, Christoph M. Friedrich, Mitchell Fulton, Finn Gaida, Francesco Galati, Christoforos Galazis, Chang Hee Gan, Zheyao Gao, Shengbo Gao, Matej Gazda, Beerend Gerats, Neil Getty, Adam Gibicar, Ryan Gifford, Sajan Gohil, Maria Grammatikopoulou, Daniel Grzech, Orhun Güley, Timo Günnemann, Chunxu Guo, Sylvain Guy, Heonjin Ha, Luyi Han, Il Song Han, Ali Hatamizadeh, Tian He, Jimin Heo, Sebastian Hitziger, SeulGi Hong, SeungBum Hong, Rian Huang, Ziyan Huang, Markus Huellebrand, Stephan Huschauer, Mustaffa Hussain, Tomoo Inubushi, Ece Isik Polat, Mojtaba Jafaritadi, SeongHun Jeong, Bailiang Jian, Yuanhong Jiang, Zhifan Jiang, Yueming Jin, Smriti Joshi, Abdolrahim Kadkhodamohammadi, Reda Abdellah Kamraoui, Inha Kang, Junghwa Kang, Davood Karimi, April Khademi, Muhammad Irfan Khan, Suleiman A. Khan, Rishab Khantwal, Kwang-Ju Kim, Timothy Kline, Satoshi Kondo, Elina Kontio, Adrian Krenzer, Artem Kroviakov, Hugo Kuijf, Satyadwyoom Kumar, Francesco La Rosa, Abhi Lad, Doohee Lee, Minho Lee, Chiara Lena, Hao Li, Ling Li, Xingyu Li, Fuyuan Liao, KuanLun Liao, Arlindo Limede Oliveira, Chaonan Lin, Shan Lin, Akis Linardos, Marius George Linguraru, Han Liu, Tao Liu, Di Liu, Yanling Liu, João Lourenço-Silva, Jingpei Lu, Jiangshan Lu, Imanol Luengo, Christina B. Lund, Huan Minh Luu and Yi Lv, Biomedical image analysis competitions: The state of current participation practice (2022), in: arXiv

[DOI]
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Pierre Fontaine, Vincent Andrearczyk, Valentin Oreiller, Daniel Abler, Joel Castelli, Oscar Acosta, R. De Crevoisier, Martin Vallìères, Mario Jreige, John O. Prior and Adrien Depeursinge, Cleaning Radiotherapy Contours for Radiomics Studies, is it Worth it? A Head and Neck Cancer Study (2022), in: Clinical and Translational Radiation Oncology, 33(153-158)

[]: IF 2021 = 4.739

Pierre Fontaine, Vincent Andrearczyk, Valentin Oreiller, Joel Castelli, Mario Jreige, John O. Prior and Adrien Depeursinge, Fully Automatic Head and Neck Cancer Prognosis Prediction in PET/CT, in: Multimodal Learning for Clinical Decision Support, pages 59-68, Springer LNCS, 2021

Alba García Seco de Herrera, Carsten Eickhoff, Vincent Andrearczyk and Henning Müller, Overview of the ImageCLEF 2018 caption prediction tasks, in: CLEF working notes, CEUR, 2018

Mara Graziani, Vincent Andrearczyk and Henning Müller, Deep learning interpretability: measuring the relevance of clinical concepts in convolutional neural networks features, Elsevier, volume 157-192, 2023

Mara Graziani, Vincent Andrearczyk and Henning Müller, Deep Learning Interpretability: Measureing the relevance of clinical concepts in CNN features, in: State of the art in neural networks, Elsevier, 2022

Mara Graziani, Vincent Andrearczyk and Henning Müller, Visualizing and interpreting feature reuse of pretrained CNNs for histopathology, in: IMVIP 2019, Dublin, Ireland, 2019

Mara Graziani, Vincent Andrearczyk and Henning Müller, Regression Concept Vectors for Bidirectional Explanations in Histopathology (2018), in: Lecture Notes in Computer Science, Workshop on Interpretability of Machine Intelligence in Medical Image Computing at MICCAI 2018(8)

[]: Best paper award

Mara Graziani, James M. Brown, Vincent Andrearczyk, Veysi Yildiz, J. Peter Campbelle, Deniz Erdogmus, Stratis Ioannidis, Michael F. Chiange, Jayashree Kalpathy-Cramer and Henning Müller, Improved interpretability for computer-aided severity assessment of retinopathy of prematurity, in: SPIE Medical Imaging, San Diego, CA, USA, 2019

Mara Graziani, Lidia Dutkiewicz, Davide Calvaresi, Jose Pereira Amorim, Katerina Yordanova, Mor Vered, Rahul Nair, Pedro H. Abreu, Tobias Blanke, Valeria Pulignano, John O. Prior, Lode Lauwaert, Wessel Reijers, Adrien Depeursinge, Vincent Andrearczyk and Henning Müller, A Global Taxonomy of Interpretable AI: Unifying the Terminology for the Technical and Social Sciences (2022), in: Artificial Intelligence Review, 56(3473–3504)

Mara Graziani, Ivan Eggel, Francois Deligand, Martin Bobák, Vincent Andrearczyk and Henning Müller, Breast Histopathology with High-Performance Computing and Deep Learning (2020), in: Computer and Informatics

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