Vincent Andrearczyk - HES SO Valais Publications

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

Marek Wodzinski, Tommaso Banzato, Manfredo Atzori, Vincent Andrearczyk, Yashin Dicente Cid und 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 und 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, Seiten 1758--1761, 2020

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

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Mara Graziani, Thomas Lompech, Henning Müller, Adrien Depeursinge und 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 und Adrien Depeursinge, Oropharynx Detection in PET-CT for Tumor Segmentation, in: Irish Machine Vision and Image Processing Conference, 2020, 2020

Mara Graziani, Henning Müller und Vincent Andrearczyk, Concept attribution: Explaining CNN decisions to physicians (2020), in: Computers in Biology and Medicine

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

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

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

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Vincent Andrearczyk, Valentin Oreiller, Martin Vallières, Joel Castelli, Hesham Elhalawani, Mario Jreige, Sarah Boughdad, John O. Prior und 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, Julien Fageot, Valentin Oreiller, Xavier Montet und Adrien Depeursinge, Local Rotation Invariance in 3D CNNs (2020), in: Medical Image Analysis, 65(101756)

[]: IF 2018 = 8.79

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Sebastian Otalora, Oscar Jimenez del Toro, Manfredo Atzori, Amjad Khan, Vincent Andrearczyk und 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 und Jayashree Kalpathy-Cramer, An Exploration of Uncertainty Information for Segmentation Quality Assessment, in: SPIE Medical Imaging 2020: Image Processing, Houston, TX, USA, Seiten 381-390, SPIE, 2020

Henning Müller, Vincent Andrearczyk, Oscar Jimenez del Toro, Anjani Dhrangadhariya, Roger Schaer und 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

Anjani Dhrangadhariya, Oscar Jimenez del Toro, Vincent Andrearczyk, Manfredo Atzori und 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 und Henning Müller, Generalizing Convolution Neural Networks on Stain Color Heterogeneous Data for Computational Pathology, in: SPIE Medical Imaging, Houston, TX, USA,, 2020

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 Vallières, Uulke A. van der Heide, Lisanne V. van Dijk, Joost van Griethuysen, Floris H. P. van Velden, Philip Whybra, Christian Richter und Steffen Löck, Standardized quantitative radiomics for high-throughput image-based phenotyping (2020), in: Radiology, 295:2(328-338)

[]: IF 2018 = 7.608

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

Sebastian Otalora, Manfredo Atzori, Vincent Andrearczyk, Amjad Khan und 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)

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

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

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

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

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

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 und Narciso Garcia, ImageCLEF 2019: Multimedia Retrieval in Medical Nature, Security and Lifelogging Applications, in: ECIR 2019, Cologne, Germany, 2019

Mara Graziani, Vincent Andrearczyk und 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

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

Oscar Perdomo, Vincent Andrearczyk, Fabrice Meriaudeau, Henning Müller und Fabio A. Gonzalez, Glaucoma Diagnosis from Eye Fundus Images Based on Deep Morphometric Feature Estimation, in: OMIA at MICCAI, 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 und 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 und Henning Müller, Overview of the ImageCLEF 2018 caption prediction tasks, in: CLEF working notes, CEUR, 2018

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

Michael T. McCann, Vincent Andrearczyk, Michael Unser und Adrien Depeursinge, Fast Rotational Sparse Coding (2018)(arXiv:1806.04374)

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Vincent Andrearczyk, Adrien Depeursinge und 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, Seiten 109-116, SPIE, 2019

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

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

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Vincent Andrearczyk, Adrien Depeursinge und 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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