Vincent Andrearczyk - HES SO Valais Publications

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

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Martin Vallières, 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 !

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

Sebastian Otalora, Oscar Jimenez del Toro, Manfredo Atzori, Amjad Khan, Vincent Andrearczyk and Henning Müller, A systematic comparison of deep learning strategies for weakly supervised Gleason grading,, in: SPIE Medical Imaging, Houstonm, TX, USA, 2020

Katharina Hoebel, Vincent Andrearczyk, Andrew Beers, Jay Patel, Ken Chang, Adrien Depeursinge, Henning Müller and Jayashree Kalpathy-Cramer, An Exploration of Uncertainty Information for Segmentation Quality Assessment, in: SPIE Medical Imaging 2020: Image Processing, Houston, TX, USA, pages 381-390, SPIE, 2020

Vincent Andrearczyk, Valentin Oreiller, Martin Vallières, 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

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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

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

Amjad Khan, Manfredo Atzori, Vincent Andrearczyk and Henning Müller, Generalizing Convolution Neural Networks on Stain Color Heterogeneous Data for Computational Pathology, in: SPIE Medical Imaging, Houston, TX, USA,, 2020

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

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

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, pages 1758--1761, 2020

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

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 !

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Bogdan Ionescu, Henning Müller, Alba García Seco de Herrera, 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, Cathal Gurrin, Adrian Clarck, Jon Chamberlain, Konstantinos Karampidis, Nikos Vasillopoulos, Carlos Roberto del Blanco, Carlos Cuevas Rodriguez, Ergina Kavallieratou and Narciso Garcia, ImageCLEF 2019: Multimedia Retrieval in Medical Nature, Security and Lifelogging Applications, in: ECIR 2019, Cologne, Germany, 2019

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, 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, pages 109-116, SPIE, 2019

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

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

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

Oscar Perdomo, Vincent Andrearczyk, Fabrice Meriaudeau, Henning Müller and Fabio A. Gonzalez, Glaucoma Diagnosis from Eye Fundus Images Based on Deep Morphometric Feature Estimation, in: OMIA at MICCAI, Granada, Spain, 2018

Sebastian Otalora, Manfredo Atzori, Vincent Andrearczyk and Henning Müller, Image Magnification Regression Using DenseNet for Exploiting Histopathology Open Access Content, in: MICCAI 2018 - Computational Pathology Workshop (COMPAY), Granada, Spain, 2018

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

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

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

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Vincent Andrearczyk, Valentin Oreiller, Mario Jreige, Martin Vallières, 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

Mara Graziani, An-Phi Nguyen, Laura O' Mahony, Henning Müller and Vincent Andrearczyk, Concept discovery and Dataset exploration with Singular Value Decomposition, ICLR Workshop on Trustworthy ML, 2023

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, Vincent Andrearczyk, Julien Fageot, John O. Prior and Adrien Depeursinge, 3D Solid Spherical Bispectrum CNNs for Biomedical Texture Analysis, 2020

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Mara Graziani, Sebastian Otalora, Henning Müller and Vincent Andrearczyk, Guiding CNNs towards Relevant Concepts by Multi-task and Adversarial Learning, arxiv, 2020

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

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

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

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Head and Neck Tumor Segmentation, Springer International Publishing, 2021

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

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