Thema: SNSF MAGE - HES SO Valais Publications

Omar S. Al-Kadi, Dimitri Van De Ville und Adrien Depeursinge, Multidimensional Texture Analysis for Improved Prediction of Ultrasound Liver Tumor Response to Chemotherapy Treatment, in: Medical Image Computing and Computer-Assisted Interventions (MICCAI), Seiten 619--626, Springer International Publishing, 2016

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

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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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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

Anaïs Badoual, Michael Unser und Adrien Depeursinge, Texture-Driven Parametric Snakes for Semi-Automatic Image Segmentation (2019), in: Computer Vision and Image Understanding, 188(102793)

[]: IF 2018 = 2.645
[]: Icy plugin and source code: https://bigwww.epfl.ch/demo/texture-snake/

Jocelyn Barker, Assaf Hoogi, Adrien Depeursinge und 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

Paul Blanc-Durand, Axel Van der Gucht, Mario Jreige, Marie Nicod-Lalonde, Marina Silva-Monteiro, John O. Prior, Alban Denys, Adrien Depeursinge und 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

Joel Castelli, Adrien Depeursinge, B. De Bari, Anne Devillers, R. De Crevoisier, J. Bourhis und John O. Prior, Metabolic Tumor Volume and Total Lesion Glycolysis in Oropharyngeal Cancer treated with definitive radiotherapy: Which threshold is the best predictor of local control ? (2017), in: Clinical Nuclear Medicine, 42:6(e281–e285)

[]: IF 2015 = 4.27

Joel Castelli, Adrien Depeursinge, Anne Devillers, B. Campillo-Gimenez, Yashin Dicente Cid, John O. Prior, Enrique Chajon, Franck Jegoux, C. Sire, Oscar Acosta, X. Sun, B. De Bari, J. Bourhis und R. De Crevoisier, PET-based predictive survival model after radiotherapy for head and neck cancer (2019), in: European Journal of Nuclear Medicine and Molecular Imaging, 46:3(638-649)

[]: IF 2016 = 7.277

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Joel Castelli, Adrien Depeursinge, Vanessa Ndoh, John O. Prior, Esat Ozsahin, Anne Devillers, Hanan Bouchaab, Enrique Chajon, R. De Crevoisier, Nathaniel Scher, Franck Jegoux, B. Laguerre, B. De Bari und J. Bourhis, A PET-based nomogram for oropharyngeal cancers (2017), in: European Journal of Cancer, 75(222-230)

[]: IF 2015 = 6.16

Dmitry Chezerov, Dmitry Goldgof, Lawrence Hall, Robert Gillies, Matther Schabath, Henning Müller und 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

Pol Cirujeda, Yashin Dicente Cid, Henning Müller, Daniel L. Rubin, Todd A. Aguilera, Billy W. Loo Jr., Maximilian Diehn, Xavier Binefa und Adrien Depeursinge, A 3-D Riesz-Covariance Texture Model for Prediction of Nodule Recurrence in Lung CT (2016), in: IEEE Transactions on Medical Imaging, 35:12(2620-2630)

[]: IF 2015 = 3.76
[]: video presentation of the paper: https://portal.klewel.com/watch/webcast/valaiswallis-ai-workshop-reproducibility-in-research/talk/9

Pol Cirujeda, Henning Müller, Daniel L. Rubin, Todd A. Aguilera, Billy W. Loo Jr., Maximilian Diehn, Xavier Binefa und Adrien Depeursinge, 3D Riesz–wavelet based Covariance descriptors for texture classification of lung nodule tissue in CT, in: 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Seiten 7909-7912, 2015

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

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

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Adrien Depeursinge, Anne C. Chin, Ann N. Leung, Donato Terrone, Michael Bristow, Glenn Rosen und Daniel L. Rubin, Automated Classification of Usual Interstitial Pneumonia using Regional Volumetric Texture Analysis in High-Resolution CT (2015), in: Investigative Radiology, 50:4(261-267)

[]: Impact Factor=4.453

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Adrien Depeursinge, Julien Fageot und 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, Seiten 1-27, Elsevier, 2017

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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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Adrien Depeursinge, Pedram Pad, Anne C. Chin, Ann N. Leung, Daniel L. Rubin, Henning Müller und Michael Unser, Optimized steerable wavelets for texture analysis of lung tissue in 3-D CT: classification of usual interstitial pneumonia, in: IEEE 12th International Symposium on Biomedical Imaging (ISBI), New York, NY, USA, Seiten 403-406, IEEE, 2015

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Adrien Depeursinge, Zsuzsanna Püspöki, John-Paul Ward und Michael Unser, Steerable Wavelet Machines (SWM): Learning Moving Frames for Texture Classification (2017), in: IEEE Transactions on Image Processing, 26:4(1626-1636)

[]: IF 2015 = 3.735
[]: Matlab code available! click on this entry to download the library.

Adrien Depeursinge, Tunde Szilágyi, Yan Liu, Kazmer Kovacs, Reena Thomas, Kristen Yeom, Nancy Fischbein, Daniel L. Rubin, Michael Iv und Olivier Gevaert, Locoregional radiogenomic models to capture gene expression heterogeneity in glioblastoma (2018), in: biorXiv

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

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Yashin Dicente Cid, Henning Müller, Alexandra Platon, Jean-Paul Janssens, Lador Frédéric, Pierre-Alexandre Poletti und Adrien Depeursinge, A Lung Graph-Model for Pulmonary Hypertension and Pulmonary Embolism Detection on DECT images, in: MICCAI Workshop on Medical Computer Vision: Algorithms for Big Data, Seiten 58-68, 2016

Yashin Dicente Cid, Henning Müller, Alexandra Platon, Pierre-Alexandre Poletti und Adrien Depeursinge, 3-D Solid Texture Classification Using Locally-Oriented Wavelet Transforms (2017), in: IEEE Transactions on Image Processing, 26:4(1899-1910)

[]: IF 2015 = 3.735
[]: Matlab code available! click on this entry to download the library.

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Julien Fageot, Virginie Uhlmann, Adrien Depeursinge, Zsuzsanna Püspöki, Daniel Sage und Michael Unser, Radial B-Splines for Optimal Detection in Images, in: ISBI Special Session on Spline Models in Biomedical Imaging, 2019

Julien Fageot, Virginie Uhlmann, Zsuzsanna Püspöki, Benjamin Beck, Michael Unser und Adrien Depeursinge, Principled Design and Implementation of Steerable Detectors (2021), in: IEEE Transactions on Image Processing, 30(4465-4478)

[]: IF 2020 = 9.34
[]: Demo page: http://bigwww.epfl.ch/algorithms/steer_n_detect/
[]: Source code: https://github.com/Biomedical-Imaging-Group/Steer-n-Detect

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Ranveer Joyseeree, Henning Müller und Adrien Depeursinge, Rotation-Covariant Tissue Analysis for Interstitial Lung Diseases Using Learned Steerable Filters: Performance Evaluation and Relevance for Diagnostic Aid (2018), in: Computerized Medical Imaging and Graphics, 64(1-11)

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Ranveer Joyseeree, Sebastian Otalora, Henning Müller und 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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Michael T. McCann, Vincent Andrearczyk, Michael Unser und Adrien Depeursinge, Fast Rotational Sparse Coding (2018)(arXiv:1806.04374)

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Sebastian Otalora, Angel Cruz Roa, John Arevalo, Manfredo Atzori, Anant Madabhushi, Alexander Judkins, Fabio González, Henning Müller und 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, Seiten 581-588, Springer International Publishing, 2015

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Roger Schaer, Henning Müller und Adrien Depeursinge, Optimized Distributed Hyperparameter Search and Simulation for Lung Texture Classification in CT Using Hadoop (2016), in: Journal of Imaging, 2:2(19)

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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 und 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

Anamaria Vizitiu, Lucian Itu, Ranveer Joyseeree, Adrien Depeursinge, Henning Müller und Constantin Suciu, GPU-Accelerated Texture Analysis Using Steerable Riesz Wavelets, in: 24th IEEE Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, Heraklion Crete, Greece, Seiten 431--434, 2016

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 Vallìères, 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