Vincent Andrearczyk - HES SO Valais Publications

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

Vincent Andrearczyk, Valentin Oreiller, Martin Vallières, Joel Castelli, Hesham Elhalawani, Mario Jreige, Sarah Boughdad, John O. Prior en 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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Mara Graziani, Ivan Eggel, Francois Deligand, Martin Bobák, Vincent Andrearczyk en Henning Müller, Breast Histopathology with High-Performance Computing and Deep Learning (2020), in: Computer and Informatics

Mara Graziani, Henning Müller en 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 en 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 en 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 en Henning Müller, Generalizing Convolution Neural Networks on Stain Color Heterogeneous Data for Computational Pathology, in: SPIE Medical Imaging, Houston, TX, USA,, 2020

Mara Graziani, Sebastian Otalora, Henning Müller en 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 en 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, Julien Fageot, Valentin Oreiller, Xavier Montet en Adrien Depeursinge, Local Rotation Invariance in 3D CNNs (2020), in: Medical Image Analysis, 65(101756)

[]: IF 2018 = 8.79

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

Adrien Depeursinge, Vincent Andrearczyk, Philip Whybra, Joost van Griethuysen, Henning Müller, Roger Schaer, Martin Vallières en 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 Vallières, Uulke A. van der Heide, Lisanne V. van Dijk, Joost van Griethuysen, Floris H. P. van Velden, Philip Whybra, Christian Richter en Steffen Löck, Standardized quantitative radiomics for high-throughput image-based phenotyping (2020), in: Radiology, 295:2(328-338)

[]: IF 2018 = 7.608

Marek Wodzinski, Tommaso Banzato, Manfredo Atzori, Vincent Andrearczyk, Yashin Dicente Cid en 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 en 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, pagina's 1758--1761, 2020

Henning Müller, Vincent Andrearczyk, Oscar Jimenez del Toro, Anjani Dhrangadhariya, Roger Schaer en 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 en Adrien Depeursinge, Exploring local rotation invariance in 3D CNNs with steerable filters, in: Medical Imaging with Deep Learning, pagina's 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 en 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 en 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 en 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 en 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, pagina's 109-116, SPIE, 2019

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

Sebastian Otalora, Manfredo Atzori, Vincent Andrearczyk, Amjad Khan en 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 en Henning Müller, Visualizing and interpreting feature reuse of pretrained CNNs for histopathology, in: IMVIP 2019, Dublin, Ireland, 2019

Vincent Andrearczyk en 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 en Adrien Depeursinge, Fast Rotational Sparse Coding (2018)(arXiv:1806.04374)

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Oscar Perdomo, Vincent Andrearczyk, Fabrice Meriaudeau, Henning Müller en 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 en 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 en 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 en Henning Müller, Overview of the ImageCLEF 2018 caption prediction tasks, in: CLEF working notes, CEUR, 2018

Mara Graziani, Vincent Andrearczyk en 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 en Michael Unser, Rotation Invariance and Directional Sensitivity: Spherical Harmonics versus Radiomics Features, in: Machine Learning in Medical Imaging (MLMI), pagina's 107--115, Springer International Publishing, 2018

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

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