Vincent Andrearczyk
The image biomarker standardization initiative: standardized quantitative radiomics for high-throughput image-based phenotyping
A Zwanenburg, M Vallières, MA Abdalah, HJWL Aerts, V Andrearczyk, ...
Radiology 295 (2), 328-338, 2020
Using filter banks in convolutional neural networks for texture classification
V Andrearczyk, PF Whelan
Pattern Recognition Letters 84, 63-69, 2016
Head and neck tumor segmentation in PET/CT: the HECKTOR challenge
V Oreiller, V Andrearczyk, M Jreige, S Boughdad, H Elhalawani, J Castelli, ...
Medical image analysis 77, 102336, 2022
Overview of the HECKTOR challenge at MICCAI 2021: automatic head and neck tumor segmentation and outcome prediction in PET/CT images
V Andrearczyk, V Oreiller, S Boughdad, CCL Rest, H Elhalawani, ...
3D head and neck tumor segmentation in PET/CT challenge, 1-37, 2021
Overview of the HECKTOR challenge at MICCAI 2020: automatic head and neck tumor segmentation in PET/CT
V Andrearczyk, V Oreiller, M Jreige, M Vallieres, J Castelli, H Elhalawani, ...
Head and Neck Tumor Segmentation: First Challenge, HECKTOR 2020, Held in …, 2021
Overview of ImageCLEF 2018: Challenges, datasets and evaluation
B Ionescu, H Müller, M Villegas, A García Seco de Herrera, C Eickhoff, ...
Experimental IR Meets Multilinguality, Multimodality, and Interaction: 9th …, 2018
Regression concept vectors for bidirectional explanations in histopathology
M Graziani, V Andrearczyk, H Müller
Understanding and Interpreting Machine Learning in Medical Image Computing …, 2018
Making radiomics more reproducible across scanner and imaging protocol variations: a review of harmonization methods
SA Mali, A Ibrahim, HC Woodruff, V Andrearczyk, H Müller, S Primakov, ...
Journal of personalized medicine 11 (9), 842, 2021
Convolutional neural network on three orthogonal planes for dynamic texture classification
V Andrearczyk, PF Whelan
Pattern Recognition 76, 36-49, 2018
Concept attribution: Explaining CNN decisions to physicians
M Graziani, V Andrearczyk, S Marchand-Maillet, H Müller
Computers in biology and medicine 123, 103865, 2020
Automatic segmentation of head and neck tumors and nodal metastases in PET-CT scans
V Andrearczyk, V Oreiller, M Vallières, J Castelli, H Elhalawani, M Jreige, ...
Medical imaging with deep learning, 33-43, 2020
Staining invariant features for improving generalization of deep convolutional neural networks in computational pathology
S Otálora, M Atzori, V Andrearczyk, A Khan, H Müller
Frontiers in bioengineering and biotechnology, 198, 2019
Overview of the ImageCLEF 2018 caption prediction tasks
A García Seco de Herrera, C Eickhof, V Andrearczyk, H Müller
Working Notes of CLEF 2018-Conference and Labs of the Evaluation Forum (CLEF …, 2018
Deep Learning in Texture Analysis and its Application to Tissue Image Classification
V Andrearczyk, P Whelan
Biomedical Texture Analysis: Fundamentals, Applications, Tools and …, 2017
Glaucoma diagnosis from eye fundus images based on deep morphometric feature estimation
O Perdomo, V Andrearczyk, F Meriaudeau, H Müller, FA González
Computational Pathology and Ophthalmic Medical Image Analysis: First …, 2018
Standardised convolutional filtering for radiomics
A Depeursinge, V Andrearczyk, P Whybra, J van Griethuysen, H Müller, ...
arXiv preprint arXiv:2006.05470, 2020
An exploration of uncertainty information for segmentation quality assessment
K Hoebel, V Andrearczyk, A Beers, J Patel, K Chang, A Depeursinge, ...
Medical Imaging 2020: Image Processing 11313, 381-390, 2020
Texture segmentation with fully convolutional networks
V Andrearczyk, PF Whelan
arXiv preprint arXiv:1703.05230, 2017
Multi-task deep segmentation and radiomics for automatic prognosis in head and neck cancer
V Andrearczyk, P Fontaine, V Oreiller, J Castelli, M Jreige, JO Prior, ...
Predictive Intelligence in Medicine: 4th International Workshop, PRIME 2021 …, 2021
Neural network training for cross-protocol radiomic feature standardization in computed tomography
V Andrearczyk, A Depeursinge, H Müller
Journal of Medical Imaging 6 (2), 024008-024008, 2019
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