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590 publications (0 read)
940 authors [view]
39 Subtopics

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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 (2024), in: arxiv

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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

Jakub Mlynar, Adrien Depeursinge, John O. Prior, Roger Schaer, Alexandre Martroye de Joly and Florian Evéquoz, Making sense of radiomics: Insights on human-AI collaboration in medical interaction from an observational user study (2024), in: Frontiers in Communication, 8

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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 Vallières 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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Federico Spagnolo, Adrien Depeursinge, Vincent Andrearczyk, Pascal Benkert, Stefanie Müller, Lutz Achtnichts, Jochen Vehoff, Giulio Di Santo, Oliver Findling, Andrew Chan, Anke Salmen, Caroline Pot, Claire Bridel, Chiara Zecca, Tobias Johannes Derfuss, Johanna M. Lieb, Luca Remonda, Franca Wagner, Maria-Isabel Vargas Gomez, Renaud Du Pasquier, Patrice Lalive, Emanuele Pravatà, Johannes Weber, Claudio Gobbi, David Leppert, Nataliia Molchanova, Meritxell Bach Cuadra, Po-Jui Lu, Mario Ocampo-Pineda, Lester Melie-Garcia, Cagol Alessandro, Ludwig Kappos, Jens Kuhle and Cristina Granziera, Identification of paramagnetic rim lesions using conventional MRI - a deep learning approach, in: 39th Congress Of The European Committee For Treatment And Research In Multiple Sclerosis (ECTRIMS), 2023

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Federico Spagnolo, Adrien Depeursinge, Henning Müller, Aysenur Akbulut, Muhamed Barakovic, Lester Melie-Garcia, Sabine Schädelin and Cristina Granziera, How far MS lesion detection and segmentation are integrated into the clinical workflow? A systematic review (2023), in: NeuroImage: Clinical, 39(103491)

[]: IF 2022: 4.2

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Vincent Andrearczyk, Luis Schiappacasse, Daniel Abler, Marek Wodzinski, Andreas Hottinger, Matthieu Raccaud, Jean Bourhis, John O. Prior, Vincent Dunet and Adrien Depeursinge, Automatic Detection and Multi-Component Segmentation of Brain Metastases in Longitudinal MRI (2024), in: Nature Scientic Reports

Federico Spagnolo, Roger Schaer, Vincent Andrearczyk, Nataliia Molchanova, Mara Graziani, Henning Müller, Meritxell Bach Cuadra, Cristina Granziera and Adrien Depeursinge, FLAIR vs MPRAGE contribution to white matter lesion automatic segmentation in MS using localized saliency maps, in: Bern Interpretable AI Symposium (BIAS), 2023

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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 Vallières, 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, pages 1-30, Springer, Cham, 2023

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Sacha Bors, Daniel Abler, Matthieu Dietz, Vincent Andrearczyk, Julien Fageot, Marie Nicod-Lalonde, Niklaus Schaefer, Robert DeKemp, Christel H. Kamani, John O. Prior and Adrien Depeursinge, Comparing various AI approaches to traditional quantitative assessment of the myocardial perfusion in [82Rb] PET for MACE prediction (2024), in: Nature Scientific Reports, 14:9644

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Vincent Andrearczyk, Valentin Oreiller, Sarah Boughdad, Catherine Cheze-Le-Rest, Olena Tankyevych, Hesham Elhalawani, Mario Jreige, John O. Prior, Martin Vallières, Dimitris Visvikis, Mathieu Hatt and Adrien Depeursinge, Automatic Head and Neck Tumor Segmentation and Outcome Prediction Relying on FDG-PET/CT Images: Findings from the Second Edition of the HECKTOR Challenge (2023), in: Medical Image Analysis, 90:1(102972)

[]: IF 2022: 10.9

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Mara Graziani, Lidia Dutkiewicz, Davide Calvaresi, Jose Pereira Amorim, Katerina Yordanova, Mor Vered, Rahul Nair, Pedro H. Abreu, Tobias Blanke, Valeria Pulignano, John O. Prior, Lode Lauwaert, Wessel Reijers, Adrien Depeursinge, Vincent Andrearczyk and Henning Müller, A Global Taxonomy of Interpretable AI: Unifying the Terminology for the Technical and Social Sciences (2022), in: Artificial Intelligence Review, 56(3473–3504)

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Daphné Faist, Mario Jreige, Valentin Oreiller, Marie Nicod-Lalonde, Niklaus Schaefer, Adrien Depeursinge and John O. Prior, Reproducibility of lung cancer radiomics features extracted from data-driven respiratory gating and free-breathing flow imaging in [18F]-FDG PET/CT (2022), in: European Journal of Hybrid Imaging, 6:1(33)

[]: IF 2022: 1.7

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Vincent Andrearczyk, Valentin Oreiller, Mario Jreige, Hesham Elhalawani, Sarah Boughdad, Catherine Cheze-Le-Rest, John O. Prior, Mathieu Hatt and Adrien Depeursinge, HEad and neCK TumOR segmentation and outcome prediction: The HECKTOR challenge, in: European Society of Radiology, 2022

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

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

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Vincent Andrearczyk, Valentin Oreiller, Sarah Boughdad, Catherine Cheze-Le-Rest, Hesham Elhalawani, Mario Jreige, John O. Prior, Martin Vallières, 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, pages 1-37, 2022

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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), pages 4731-4735, 2022

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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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Michael Bach, Christoph Aberle, Adrien Depeursinge, Oscar Jimenez del Toro, Roger Schaer, Kyriakos Flouris, Ender Konukoglu, Henning Müller and Markus Obmann, 3D-Printed Iodine-Ink CT Phantom for Radiomics Feature Extraction - Advantages and Challenges (2023), in: Medical Physics, 50:9(5682-5697)

[]: IF 2023: 4.506

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Virginie Uhlmann, Zsuzsanna Püspöki, Adrien Depeursinge, Michael Unser, Daniel Sage and Julien Fageot, Steer'n'Detect: Fast 2D Template Detection with Accurate Orientation Estimation (2022), in: Bioinformatics, 38:11(3146–3148)

[]: IF 2019 = 5.61
[]: Demo page: http://bigwww.epfl.ch/algorithms/steer_n_detect/
[]: Source code: https://github.com/Biomedical-Imaging-Group/Steer-n-Detect
[]: Zenodo: https://zenodo.org/records/10078907

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Daniel Abler, Vincent Andrearczyk, Valentin Oreiller, Javier Barranco Garcia, Diem Vuong, Stephanie Tanadini-Lang, Matthias Guckenberger, Mauricio Reyes and Adrien Depeursinge, Comparison of MR preprocessing strategies and sequences for radiomics-based MGMT prediction, in: Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries (MICCAI/BrainLes 2021), Cham, pages 367–380, Springer International Publishing, 2022

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Kyriakos Flouris, Oscar Jimenez del Toro, Christoph Aberle, Michael Bach, Roger Schaer, Markus Obmann, Bram Stieltjes, Henning Müller, Adrien Depeursinge and Ender Konukoglu, Assessing radiomics feature stability with simulated CT acquisitions (2022), in: Scientific Reports, 12:1(4732)

[]: IF 2020 = 4.379

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Pierre Fontaine, Vincent Andrearczyk, Valentin Oreiller, Daniel Abler, Joel Castelli, Oscar Acosta, R. De Crevoisier, Martin Vallières, Mario Jreige, John O. Prior and Adrien Depeursinge, Cleaning Radiotherapy Contours for Radiomics Studies, is it Worth it? A Head and Neck Cancer Study (2022), in: Clinical and Translational Radiation Oncology, 33(153-158)

[]: IF 2021 = 4.739

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Daniel Abler, Roger Schaer, Valentin Oreiller, Himanshu Verma, Julien Reichenbach, Orfeas Aidonopoulos, Florian Evéquoz, Mario Jreige, John O. Prior and Adrien Depeursinge, QuantImage v2: A Comprehensive and Integrated Physician-Centered Cloud Platform for Radiomics and Machine Learning Research (2023), in: European Radiology Experimental, 7:16

[]: IF 2022: 3.75

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Roger Schaer, Valentin Oreiller, Daniel Abler, Himanshu Verma, Julien Reichenbach, Florian Evéquoz, Mario Jreige, John O. Prior and Adrien Depeursinge, QuantImage v2: A Clinician-in-the-loop Cloud Platform for Radiomics Research, in: European Society of Radiology, 2022

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Valentin Oreiller, Vincent Andrearczyk, Mario Jreige, Sarah Boughdad, Hesham Elhalawani, Joel Castelli, Martin Vallières, Simeng Zhu, Juanying Xie, Ying Peng, Andrei Iantsen, Mathieu Hatt, Yading Yuan, Jun Ma, Xiaoping Yang, Chinmay Rao, Suraj Pai, Kanchan Ghimire, Xue Feng, Mohamed A. Naser, Clifton D. Fuller, Fereshteh Yousefirizi, Arman Rahmim, Huai Chen, Lisheng Wang, John O. Prior and Adrien Depeursinge, Head and Neck Tumor Segmentation in PET/CT: The HECKTOR Challenge (2022), in: Medical Image Analysis, 77(102336)

[]: IF 2020 = 8.545

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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, pages 147-156, Springer LNCS, 2021

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Pierre Fontaine, Vincent Andrearczyk, Valentin Oreiller, Joel Castelli, Mario Jreige, John O. Prior and Adrien Depeursinge, Fully Automatic Head and Neck Cancer Prognosis Prediction in PET/CT, in: Multimodal Learning for Clinical Decision Support, pages 59-68, Springer LNCS, 2021

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Himanshu Verma, Jakub Mlynar, Roger Schaer, Julien Reichenbach, Mario Jreige, John O. Prior, Florian Evéquoz and Adrien Depeursinge, Rethinking the Role of AI with Physicians in Oncology: Revealing Perspectives from Clinical and Research Workflows, in: ACM CHI 2023, 2023

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Oscar Jimenez del Toro, Christoph Aberle, Michael Bach, Roger Schaer, Markus Obmann, Kyriakos Flouris, Ender Konukoglu, Bram Stieltjes, Henning Müller and Adrien Depeursinge, The discriminative power and stability of radiomics features with CT variations: Task-based analysis in an anthropomorphic 3D-printed CT phantom (2021), in: Investigative Radiology, 56:12(820-825)

[]: IF 2020 = 5.156

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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)

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Roger Schaer, Valentin Oreiller, Orfeas Aidonopoulos, John O. Prior and Adrien Depeursinge, QuantImage v2: an Open-Source and Web-Based Integrated Platform for Clinical Radiomics Research, in: Joint scientific session SSRMP/SGR-SSR, 2021

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Oscar Jimenez del Toro, Michael Bach, Christoph Aberle, Roger Schaer, Markus Obmann, Kyriakos Flouris, Ender Konukoglu, Bram Stieltjes, Henning Müller and Adrien Depeursinge, Assessment of the stability and discriminative power of radiomics features in liver lesions using an anthropomorphic 3D-printed CT phantom, in: Scientific session SGR-SSR, 2021

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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

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Oscar Jimenez del Toro, Christoph Aberle, Michael Bach, Roger Schaer, Markus Obmann, Kyriakos Flouris, Ender Konukoglu, Bram Stieltjes, Adrien Depeursinge and Henning Müller, Revealing most suitable CT radiomics features for retrospective studies with heterogeneous datasets, in: European Congress of Radiology (ECR) 2021, ONLINE edition, 2021

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Pierre Fontaine, Oscar Acosta, Joel Castelli, R. De Crevoisier, Henning Müller and Adrien Depeursinge, The Importance of Feature Aggregation in Radiomics: A Head and Neck Cancer Study (2020), in: Nature Scientific Reports, 10:19679

[]: IF 2019 = 3.998

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Sylvie Belleville, Marc Cuesta, Mélanie Bieler-Aeschlimann, Katia Giacomino, Antoine Widmer, Anne-Gabrielle {Mittaz Hager}, Daniel Perez-Marcos, Sylvain Cardin, Benjamin Boller, Nathalie Bier, Mylène Aubertin-Leheudr and Jean-François Démonet, Rationale and protocol of the StayFitLonger study: a multicentre trial to measure efficacy and adherence of a home-based computerised multidomain intervention in healthy older adults. (2020), in: BMC Geriatrics

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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

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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

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Oscar Jimenez del Toro, Yashin Dicente Cid, Alexandra Platon, Anne-Lise Hachulla, Lador Frédéric, Pierre-Alexandre Poletti and Henning Müller, A lung graph model for the radiological assessment of chronic thromboembolic pulmonary hypertension in CT (2020), in: Computers in Biology and Medicine(103962)

[]: (IF 2019: 3.434)

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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

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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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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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Gwenaelle Creff, Anne Devillers, Adrien Depeursinge, Xavier Palard-Novello, Oscar Acosta, Franck Jegoux and Joel Castelli, Evaluation of the Prognostic Value of FDG PET/CT Parameters for Patients with Surgically Treated Head and Neck Cancer: A Systematic Review (2020), in: JAMA Otolaryngology - Head and Neck Surgery, 146:5(471-479)

[]: IF 2019 = 3.295

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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, 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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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

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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 and Steffen Löck, Standardized quantitative radiomics for high-throughput image-based phenotyping (2020), in: Radiology, 295:2(328-338)

[]: IF 2018 = 7.608

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Roger Schaer, Sebastian Otalora, Oscar Jimenez del Toro, Manfredo Atzori and Henning Müller, Deep learning based retrieval system for gigapixel histopathology cases and open access literature (2019), in: Pathology Informatics

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