Vincent Andrearczyk - HES SO Valais Publications

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Primeiro nome(s):	Vincent
Sobrenome(s):	Andrearczyk
Instituto:	II

| 1-50 | 51-96 |

Maria Martin Asiain, Mohammadreza Amirian, Oscar Jimenez del Toro, Christoph Aberle, Roger Schaer, Michael Bach, Markus Obmann, Kyriakos Flouris, Henning Müller, Bram Stieltjes, Ender Konukoglu, Vincent Andrearczyk and Adrien Depeursinge, Impact of CT dose on AI performance: A comparison of radiomics, deep, and foundation models in a multi-centric anthropomorphic phantom study (2026), in: Medical Physics

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

Federico Spagnolo, Nataliia Molchanova, Roger Schaer, Mario Ocampo-Pineda, Meritxell Bach Cuadra, Lester Melie-Garcia, Cristina Granziera, Vincent Andrearczyk and Adrien Depeursinge, Instance-level explanations in multiple sclerosis lesion segmentation: a novel localized saliency map, in: ISMRM 2024, 2024

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Federico Spagnolo, Nataliia Molchanova, Roger Schaer, Meritxell Bach Cuadra, Mario Ocampo-Pineda, Lester Melie-Garcia, Cristina Granziera, Vincent Andrearczyk and Adrien Depeursinge, Instance-level quantitative saliency in multiple sclerosis lesion segmentation (2026), in: Nature Scientific Reports

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Mara Graziani, Thomas Lompech, Henning Müller, Adrien Depeursinge and Vincent Andrearczyk, Interpretable CNN Pruning for Preserving Scale-Covariant Features in Medical Imaging, in: Workshop on Interpretability of Machine Intelligence in Medical Image Computing at MICCAI 2020, 2020

Mara Graziani, Henning Müller and Vincent Andrearczyk, Interpreting intentionally flawed models with linear probes, in: ICCV workshop on statistical deep learning in computer vision, Seoul, Korea, 2019

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, páginas 109-116, SPIE, 2019

Mara Graziani, Sebastian Otalora, Stéphane Marchand-Maillet, Henning Müller and Vincent Andrearczyk, Learning Interpretable Microscopic Features of Tumor by Multi-task Adversarial CNNs To Improve Generalization (2023), in: Machine Learning for Biomedical Imaging (MELBA), 2

[DOI]

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

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

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

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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

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Jianning Li, Antonio Pepe, Christina Gsaxner, Gijs Luijten, Yuan Jin, Narmada Ambigapathy, Enrico Nasca, Naida Solak, Gian Marco Melito, Afaque R. Memon, Xiaojun Chen, Jan Stefan Kirschke, Ezequiel de la Rosa, Patrich Ferndinand Christ, Hongwei Bran Li, David G. Ellis, Michele R. Aizenberg, Sergios Gatidis, Thomas Kuestner, Nadya Shusharina, Nicholas Heller, Vincent Andrearczyk, Adrien Depeursinge, Mathieu Hatt, Anjany Sekuboyina, Maximilian Loeffler, Hans Liebl, Reuben Dorent, Tom Vercauteren, Jonathan Shapey, Aaron Kujawa, Stefan Cornelissen, Patrick Langenhuizen, Achraf Ben-Hamadou, Ahmed Rekik, Sergi Pujades, Edmond Boyer, Federico Bolelli, Costantino Grana, Luca Lumetti, Hamidreza Salehi, Jun Ma, Yao Zhang, Ramtin Gharleghi, Susann Beier, Eduardo A. Garza-Villarreal, Thania Balducci, Diego Angeles-Valdez, Roberto Souza, Leticia Rittner, Richard Frayne, Yuanfeng Ji, Soumick Chatterjee, Andreas Nuernberger, Joao Pedrosa, Carlos Ferreira, Guilherme Aresta, Antonio Cunha, Aurelio Campilho, Yannick Suter, Jose Garcia, Alain Lalande, Emmanuel Audenaert, Claudia Krebs, Timo Van Leeuwen, Evie Vereecke, Rainer Roehrig, Frank Hoelzle, Vahid Badeli, Kathrin Krieger, Matthias Gunzer, Jianxu Chen, Amin Dada, Miriam Balzer, Jana Fragemann, Frederic Jonske, Moritz Rempe, Stanislav Malorodov, Fin H. Bahnsen, Constantin Seibold, Alexander Jaus, Ana Sofia Santos, Mariana Lindo, Andre Ferreira, Victor Alves, Michael Kamp, Amr Abourayya, Felix Nensa, Fabian Hoerst, Alexander Brehmer, Lukas Heine, Lars E. Podleska, Matthias A. Fink, Julius Keyl, Konstantinos Tserpes, Moon-Sung Kim, Shireen Elhabian, Hans Lamecker, Dzenan Zukic, Beatriz Paniagua, Christian Wachinger, Martin Urschler, Luc Duong, Jakob Wasserthal, Peter F. Hoyer, Oliver Basu, Thomas Maal, Max J. H. Witjes, Ping Luo, Bjoern Menze, Mauricio Reyes, Christos Davatzikos, Behrus Puladi, Jens Kleesiek and Jan Egger, MedShapeNet -- A Large-Scale Dataset of 3D Medical Shapes for Computer Vision, 2023

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Valentin Oreiller, Julien Fageot, Vincent Andrearczyk, John O. Prior and Adrien Depeursinge, Multi-Organ Nucleus Segmentation Using a Locally Rotation Invariant Bispectral U-Net, in: Medical Imaging with Deep Learning, 2022

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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, páginas 147-156, Springer LNCS, 2021

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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)

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Mara Graziani, Thomas Lompech, Henning Müller, Adrien Depeursinge and Vincent Andrearczyk, On the Scale Invariance in State of the Art CNNs Trained on ImageNet (2021), in: Special Issue "Interpretable and Annotation-Efficient Learning for Medical Image Computing" in Machine Learning and Knowledge Extraction:3(374–391)

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

Bogdan Ionescu, Henning Müller, Mauricio Villegas, Alba García Seco de Herrera, Carsten Eickhoff, Vincent Andrearczyk, Yashin Dicente Cid, Vitali Liauchuk, Vassili Kovalev, Sadid A. Hasan, Yuan Ling, Oladimeji Farri, Joey Liu, Matthew Lungren, Duc-Tien Dang-Nguyen, Luca Piras, Michael Riegler, Liting Zhou, Mathias Lux and Cathal Gurrin, Overview of ImageCLEF 2018: Challenges, Datasets and Evaluation, in: CLEF conference proceeding, Avignon, France, Springer, 2018

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, páginas 1-21, 2021

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, páginas 1-37, 2022

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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, páginas 1-30, Springer, Cham, 2023

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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

Martin Vallìères, Philip Whybra, Vincent Andrearczyk, Roger Schaer, Henning Müller, Adrien Depeursinge and Alex Zwanenburg, Radiomics Analysis Using The Image Biomarker Standardization Initiative (IBSI) Benchmarks And Guidelines, in: Radiological Society of North America (RSNA) 2021 Annual Meeting, 2021

[]: Won a Cum Laude Education Exhibit Award !

Eloise Sychold, Clemence de Cournuaud, Nicolas Danthez, Rémy Kinj, Véronique Vallet, Maud Gondre, Andreas Hottinger, Vincent Andrearczyk, Vincent Dunet, Adrien Depeursinge and Luis Schiappacasse, RDTA-08 MULTI-SEQUENTIAL STEREOTACTIC RADIOSURGERY (SRS) FOR BRAIN METASTASES: 10-YEAR EXPERIENCE FROM THE CHUV (LAUSANNE, SWITZERLAND) BRAIN METASTASIS CLINIC (2025), in: Neuro-Oncology Advances, 7:Supplement_2(ii26-ii26)

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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

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), páginas 107--115, Springer International Publishing, 2018

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

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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), páginas 4731-4735, 2022

Mara Graziani, Iam Palatnik de Sousa, Marley M Vellasco BR, Eduardo Costa da Silva, Henning Müller and Vincent Andrearczyk, Sharpening Local Interpretable Model-agnostic Explanations for Histopathology: Improved Understandability and Reliability, in: MICCAI 2021, Springer, 2021

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, páginas 37-44, 2019

Sebastian Otalora, Manfredo Atzori, Vincent Andrearczyk, Amjad Khan and Henning Müller, Staining invariant features for improving generalization of deep convolutional neural networks in computational pathology (2019), in: Frontiers in Bioengineering and Biotechnology-Bioinformatics and Computational Biology

[]: (IF 2017= 5.122)

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

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Alex Zwanenburg, Mahmoud A. Abdalah, Hugo Aerts, Vincent Andrearczyk, Aditya Apte, Saeed Ashrafinia, Roelof J. Beukinga, Ronald Boellaard, Marta Bogowicz, Luca Boldrini, Adrien Depeursinge, Marie-Charlotte Desseroit, Nicola Dinapoli, Cuong Viet Dinh, Sebastian Echegaray, Issam El Naqa, Andriy Y. Fedorov, Roberto Gatta, Robert J. Gillies, Matthias Guckenberger, Nils Gählert, Michael Götz, Mathieu Hatt, Fabian Isensee, Philippe Lambin, Stefan Leger, Ralph T. H. Leijenaar, Jacopo Lenkowicz, Fiona Lippert, Are Losnegård, Klaus H. Maier-Hein, Olivier Morin, Henning Müller, Sandy Napel, Arman Rahmim, Arvind U. K. Rao, Nanna M. Sijtsema, Jairo Socarras Fernandez, Emiliano Spezi, Roel J. H. M Steenbakkers, Stephanie Tanadini-Lang, Daniela Thorwarth, Esther G. C. Troost, Taman Upadhaya, Vincenzo Valentini, Martin Vallìères, Uulke A. van der Heide, Lisanne V. van Dijk, Joost van Griethuysen, Floris H. P. van Velden, Philip Whybra, Christian Richter and Steffen Löck, Standardized quantitative radiomics for high-throughput image-based phenotyping (2020), in: Radiology, 295:2(328-338)

[]: IF 2018 = 7.608

Philip Whybra, Roger Schaer, Adrien Depeursinge, Vincent Andrearczyk, Henning Müller, Martin Vallìères and Alex Zwanenburg, The Image Biomarker Standardisation Initiative (IBSI) On Reproducible Convolutional Radiomics, in: European Society of Radiology, 2022

Philip Whybra, Alex Zwanenburg, Vincent Andrearczyk, Roger Schaer, Aditya P Apte, Alexandre Ayotte, Bhakti Baheti, Spyridon Bakas, Andrea Bettinelli, Ronald Boellaard, Luca Boldrini, Irène Buvat, Gary J R Cook, Florian Dietsche, Nicola Dinapoli, Hubert S Gabryś, Vicky Goh, Matthias Guckenberger, Mathieu Hatt, Mahdi Hosseinzadeh, Aditi Iyer, Jacopo Lenkowicz, Mahdi A L Loutfi, Steffen Löck, Francesca Marturano, Olivier Morin, Christophe Nioche, Fanny Orlhac, Sarthak Pati, Arman Rahmim, Masoud Seyed, Christopher G Rookyard, Mohammad R Salmanpour, Andreas Schindele, Isaac Shiri, Emiliano Spezi, Stephanie Tanadini-Lang, Florent Tixier, Taman Upadhaya, Vincenzo Valentini, Joost J M van Griethuysen, Fereshteh Yousefirizi, Habib Zaidi, Henning Müller, Martin Vallìères and Adrien Depeursinge, The image biomarker standardization initiative: Standardized convolutional filters for reproducible radiomics and enhanced clinical insights (2024), in: Radiology, 310:2

[]: IF 2022: 19.7

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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

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Marek Wodzinski, Tommaso Banzato, Manfredo Atzori, Vincent Andrearczyk, Yashin Dicente Cid and Henning Müller, Training a deep neural network for small and highly heterogeneous MRID datasets for cancer grading, in: EMBC Conference, IEEE, 2020

Marek Wodzinski, Tommaso Banzato, Manfredo Atzori, Vincent Andrearczyk, Yashin Dicente Cid and Henning Müller, Training Deep Neural Networks for Small and Highly Heterogeneous MRI Datasets for Cancer Grading, in: 2020 42nd Annual International Conference of the IEEE Engineering in Medicine \& Biology Society (EMBC), IEEE, páginas 1758--1761, 2020

Mara Graziani, Laura O' Mahony, An-Phi Nguyen, Henning Müller and Vincent Andrearczyk, Uncovering Unique Concept Vectors through Latent Space Decomposition

Henning Müller, Vincent Andrearczyk, Oscar Jimenez del Toro, Anjani Dhrangadhariya, Roger Schaer and Manfredo Atzori, Using Publicly Available Medical Images from the Open Access Literature and Social Networks for Model Training and Knowledge Extraction, in: Multimedia Modeling (MMM 2020), Seoul, Korea, 2020

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

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

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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)

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