Adrien Depeursinge - HES SO Valais Publications

Imon Banerjee, Sadhika Malladi, Daniela Lee, Adrien Depeursinge, Melinda Telli, Jafi Lipson, Daniel Golden and Daniel L. Rubin, Assessing Treatment Response in Triple Negative Breast Cancer from Quantitative Image Analysis in Perfusion MRI (2017), in: Journal of Medical Imaging, 5:1(5-10)

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Gwenaelle Creff, Franck Jegoux, Xavier Palard, Adrien Depeursinge, Ronan Abgral, Remi Marianowski, Thomas Eugene, Olivier Malard, R. De Crevoisier, Anne Devillers and Joel Castelli, FDG-PET/CT-based prognostic survival model after surgery for head and neck cancer (2022), in: Journal of Nuclear Medicine, 63:1

[]: IF 2020 = 10.057

Sarah Boughdad, Valentin Oreiller, MARIE MEYER, Niklaus Schaefer, Marie Nicod-Lalonde, Mario Jreige, Adrien Depeursinge and John O. Prior, Impact of a Gaussian filter applied to post-reconstruction PET images on radiomic features to predict complete pathological response in breast cancer (2020), in: Journal of Nuclear Medicine, 61:supplement 1(606--606)

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Sarah Boughdad, Valentin Oreiller, MARIE MEYER, Niklaus Schaefer, Marie Nicod Lalonde, Mario Jreige, Adrien Depeursinge and John O. Prior, Impact of a Gaussian filter applied to post-reconstruction PET on radiomic features in assessing tumor heterogeneity in breast cancer. (2020), in: Journal of Nuclear Medicine, 61:supplement 1(612--612)

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Mario Jreige, Valentin Oreiller, Igor Letovanec, Niklaus Schaefer, Adrien Depeursinge and John O. Prior, PET/CT Radiomics predict Pulmonary Lymphangitic Carcinomatosis (PLC) in Non-Small Cell Lung Cancer (NSCLC) (2020), in: Journal of Nuclear Medicine, 61:supplement 1(1311--1311)

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Henning Müller and Adrien Depeursinge, La recherche d’images en plusieurs dimensions (2011), in: Market/IBCom

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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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, 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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Ranveer Joyseeree, Sebastian Otalora, Henning Müller and Adrien Depeursinge, Fusing Learned Representations from Riesz and Deep CNNs for Lung Tissue Classification (2019), in: Medical Image Analysis, 56(172-183)

[]: IF 2017 = 5.356

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Jocelyn Barker, Assaf Hoogi, Adrien Depeursinge and Daniel L. Rubin, Automated Classification of Brain Tumor Type in Whole-Slide Digital Pathology Images Using Local Representative Tiles (2016), in: Medical Image Analysis, 30(60-71)

[]: IF 2014 = 3.654

Camille Kurtz, Adrien Depeursinge, Sandy Napel, Christopher F. Beaulieu and Daniel L. Rubin, On combining visual and ontological similarities for medical image retrieval applications (2014), in: Medical Image Analysis, 18:7(1082–1100)

[]: Impact Factor=4.087

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Adrien Depeursinge, Antonio Foncubierta-Rodríguez, Dimitri Van De Ville and Henning Müller, Three-dimensional solid texture analysis in biomedical imaging: Review and opportunities (2014), in: Medical Image Analysis, 18:1(176-196)

[]: Impact Factor=4.087

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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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Adrien Depeursinge, Masahiro Yanagawa, Ann N. Leung and Daniel L. Rubin, Predicting Adenocarcinoma Recurrence Using Computational Texture Models of Nodule Components in Lung CT (2015), in: Medical Physics, 42:4(2054-2063)

[]: Impact Factor=3.012

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Antonio Foncubierta-Rodríguez, Henning Müller and Adrien Depeursinge, Retrieval of high-dimensional visual data: current state, trends and challenges ahead (2014), in: Multimedia Tools and Applications, 69:2(539-567)

[]: Impact Factor=1.014

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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 (2025), in: Nature Scientic Reports

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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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

Dmitry Chezerov, Dmitry Goldgof, Lawrence Hall, Robert Gillies, Matther Schabath, Henning Müller and Adrien Depeursinge, Revealing Tumor Habitats from Texture Heterogeneity Analysis for Classification of Lung Cancer Malignancy and Aggressiveness (2019), in: Nature Scientific Reports, 9:1(4500)

[]: IF 2016 = 4.259

Vincent Andrearczyk, Luis Schiappacasse, Jean Bourhis, John O. Prior, Michel Cuendet, Andreas Hottinger, Vincent Dunet and Adrien Depeursinge, The value of AI for assessing longitudinal brain metastases treatment response (2025), in: Neuro-Oncology Advances

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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Paul Blanc-Durand, Axel Van der Gucht, Mario Jreige, Marie Nicod-Lalonde, Marina Silva-Monteiro, John O. Prior, Alban Denys, Adrien Depeursinge and Niklaus Schaefer, Signature of Survival: A 18F-FDG PET Based Whole-Liver Radiomics Analysis Predicts Survival After 90Y-TARE for Hepatocellular Carcinoma (2017), in: OncoTarget, 9:4(4549-4558)

[]: IF 2016 = 5.168

Xin Zhou, Adrien Depeursinge and Henning Müller, Hierarchical classification using a frequency-based weighting and simple visual features (2008), in: Pattern Recognition Letters, 29:15(2011-2017)

[]: Impact Factor: 0.853 (2007)

Xin Zhou, Mikko Juhani Pitkanen, Adrien Depeursinge and Henning Müller, A Medical Image Retrieval Application Using Grid Technologies To Speed Up Feature Extraction in Medical Image Retrieval (2009), in: Philippine Journal of Information Technology

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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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

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

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)

Adrien Depeursinge, Jimison Iavindrasana, Herizo Andriambololoniaina, Pierre-Alexandre Poletti, Alexandra Platon, Antoine Geissbuhler and Henning Müller, A framework for diagnosing interstitial lung diseases in HRCT : the TALISMAN project (2008), in: Swiss Medical Informatics, 64(17-20)

Jimison Iavindrasana, Adrien Depeursinge, Rodolphe Meyer, Stéphane Spahni, Antoine Geissbuhler and Henning Müller, How clinical information systems can support life science research (2008), in: Swiss Medical Informatics, 64(21-24)

Pierre Starkov, Todd A. Aguilera, Daniel Golden, David B. Shultz, Nicholas Trakul, Peter G. Maxim, Quynh-Thu Le, Billy W. Loo Jr., Maximilian Diehn, Adrien Depeursinge and Daniel L. Rubin, The Use of Texture Based Radiomics CT Analysis to Predict Outcomes in Early-Stage Non-Small Cell Lung Cancer Treated with Stereotactic Ablative Radiotherapy (2018), in: The British Journal of Radiology, 92:1094(20180228)

[]: IF 2016 = 2.05

Adrien Depeursinge, Benedikt Fischer, Henning Müller and Thomas M. Deserno, Prototypes for content-based image retrieval in clinical practice (2011), in: The Open Medical Informatics Journal (TOMIJ), 5(58-72)

Jimison Iavindrasana, Gilles Cohen, Adrien Depeursinge, Henning Müller, Rodolphe Meyer and Antoine Geissbuhler, Clinical Data Mining: a Review (2009), in: Yearbook of Medical Informatics(121-133)

[]: Impact Factor: 1.451 (2007)

Adrien Depeursinge, Omar S. Al-Kadi and J Ross Mitchell, Biomedical Texture Analysis: Fundamentals, Applications and Tools, Elsevier, Elsevier-MICCAI Society Book series, 2017

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Fan Zhang, Yang Song, Weidong Cai, Adrien Depeursinge and Henning Müller, Text- and content-based medical image retrievals in the VISCERAL retrieval benchmark, Springer, 2017

Adrien Depeursinge, Henning Müller and Antonio Foncubierta-Rodríguez, Yearbook 2012 section article, Yearbook of Medical Informatics, 2012

Adrien Depeursinge and Julien Fageot, Biomedical Texture Operators and Aggregation Functions: A Methodological Review and User’s Guide, in: Biomedical Texture Analysis: Fundamentals, Applications and Tools, pages 55-94, Elsevier, 2017

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Adrien Depeursinge, Julien Fageot and Omar S. Al-Kadi, Fundamentals of Texture Processing for Biomedical Image Analysis: A General Definition and Problem Formulation, in: Biomedical Texture Analysis: Fundamentals, Applications and Tools, pages 1-27, Elsevier, 2017

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Adrien Depeursinge, Multi-Scale and Multi-Directional Biomedical Texture Analysis: Finding the Needle in the Haystack, in: Biomedical Texture Analysis: Fundamentals, Applications and Tools, pages 29-53, Elsevier, 2017

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Yashin Dicente Cid, Joel Castelli, Roger Schaer, Nathaniel Scher, Anastasia Pomoni, John O. Prior and Adrien Depeursinge, QuantImage: An Online Tool for High-Throughput 3D Radiomics Feature Extraction in PET-CT, in: Biomedical Texture Analysis: Fundamentals, Applications and Tools, pages 349-377, Elsevier, 2017

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Roger Schaer, Yashin Dicente Cid, Emel Alkim, Sheryl John, Daniel L. Rubin and Adrien Depeursinge, Web-Based Tools for Exploring the Potential of Quantitative Imaging Biomarkers in Radiology: Intensity and Texture Analysis on the ePAD Platform, in: Biomedical Texture Analysis: Fundamentals, Applications and Tools, pages 379-410, Elsevier, 2017

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Sebastian Otalora, Angel Cruz Roa, John Arevalo, Manfredo Atzori, Anant Madabhushi, Alexander Judkins, Fabio González, Henning Müller and Adrien Depeursinge, Combining Unsupervised Feature Learning and Riesz Wavelets for Histopathology Image Representation: Application to Identifying Anaplastic Medulloblastoma, in: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015, pages 581-588, Springer International Publishing, 2015

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Oscar Jimenez del Toro, Antonio Foncubierta-Rodríguez, Maria-Isabel Vargas Gomez, Henning Müller and Adrien Depeursinge, Epileptogenic lesion quantification in MRI using contralateral 3D texture comparisons, in: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2013, pages 353-360, Springer Berlin Heidelberg, 2013

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Adrien Depeursinge and Henning Müller, Fusion Techniques for Combining Textual and Visual Information Retrieval, in: ImageCLEF, pages 95-114, Springer Berlin Heidelberg, 2010

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Federico Spagnolo, Aarushi Bhardwaj, Pedro M. Gordaliza, Po-Jui Lu, Mario Ocampo-Pineda, Meritxell Bach Cuadra, Xinjie Chen, Batuhan Ayci, Alessandro Cagol, Vincent Andrearczyk, Adrien Depeursinge and Cristina Granziera, Deep-PRL: a deep learning network for the identification of paramagnetic rim lesions in multiple sclerosis, in: ISMRM 2025, 2025