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publications
Dense motion estimation of the heart based on cumulants
Mathieu Rubeaux, Jean-Claude Nunes, Laurent Albera, Mireille Garreau, "Dense motion estimation of the heart based on cumulants." In the proceedings of Computers in Cardiology, 2009, 2009.
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Edgeworth-based approximation of Mutual Information for medical image registration
Mathieu Rubeaux, Jean-Claude Nunes, Laurent Albera, Mireille Garreau, "Edgeworth-based approximation of Mutual Information for medical image registration." In the proceedings of 2010 2nd International Conference on Image Processing Theory, Tools and Applications, 2010.
Approximation De L'information Mutuelle Basée Sur Un Développement D'edgeworth À L'ordre 3: Application Au Recalage Non-Rigide D'images Médicales.
M. Rubeaux, Jean-Claude Nunes, Laurent Albera, Mireille Garreau, "Approximation De L'information Mutuelle Basée Sur Un Développement D'edgeworth À L'ordre 3: Application Au Recalage Non-Rigide D'images Médicales.." In the proceedings of RITS 2011 (Colloque National Recherche en Imagerie et Technologies pour la Santé), 2011.
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Approximation de l'Information Mutuelle basée sur le développement d'Edgeworth: application au recalage d'images médicales.
Mathieu Rubeaux, "Approximation de l'Information Mutuelle basée sur le développement d'Edgeworth: application au recalage d'images médicales.." Université Rennes 1, 2011.
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Numerical phantom generation to evaluate non-rigid CT/CBCT registration algorithms for prostate cancer radiotherapy
Mathieu Rubeaux, Guillaume Cazoulat, Aurélien Duménil, Caroline Lafond, Oscar Acosta, Renaud Crevoisier, Antoine Simon, Pascal Haigron, "Numerical phantom generation to evaluate non-rigid CT/CBCT registration algorithms for prostate cancer radiotherapy." In the proceedings of first MICCAI workshop on Image-Guidance and Multimodal Dose Planning in Radiation Therapy, 2012.
Evaluation of non-rigid constrained CT/CBCT registration algorithms for delineation propagation in the context of prostate cancer radiotherapy
Mathieu Rubeaux, Antoine Simon, Khemara Gnep, Jérémy Colliaux, Oscar Acosta, Renaud De, Pascal Haigron, "Evaluation of non-rigid constrained CT/CBCT registration algorithms for delineation propagation in the context of prostate cancer radiotherapy." In the proceedings of SPIE Medical Imaging, 2013.
Medical image registration using Edgeworth-based approximation of Mutual Information
M. Rubeaux, J.-C. Nunes, L. Albera, M. Garreau, "Medical image registration using Edgeworth-based approximation of Mutual Information." IRBM, 2014.
Dual-gated motion-frozen cardiac PET with flurpiridaz F 18
Piotr Slomka, Mathieu Rubeaux, Ludovic Le, Damini Dey, Joel Lazewatsky, Tinsu Pan, Marc Dweck, David Newby, Guido Germano, Daniel Berman, "Dual-gated motion-frozen cardiac PET with flurpiridaz F 18." Journal of Nuclear Medicine, 2015.
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“Motion-frozen” 18F-sodium fluoride PET for imaging coronary atherosclerotic plaques
Mathieu Rubeaux, Nikhil Joshi, Marc Dweck, Alison Fletcher, Manish Motwani, Guido Germano, Damini Dey, Daniel Berman, David Newby, Piotr Slomka, "“Motion-frozen” 18F-sodium fluoride PET for imaging coronary atherosclerotic plaques." In the proceedings of Journal of Nuclear Medicine, 2015.
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Thalamic volume as a biomarker for disorders of consciousness
Mathieu Rubeaux, Jamuna Mahalingam, Francisco Gomez, Marvin Nelson, Audrey Vanhaudenhuyse, Marie-Aurélie Bruno, Olivia Gosseries, Steven Laureys, Andrea Soddu, Natasha Lepore, "Thalamic volume as a biomarker for disorders of consciousness." In the proceedings of Tenth International Symposium on Medical Information Processing and Analysis, 2015.
Automatic valve plane localization in myocardial perfusion SPECT images using machine learning
Julian Betancur, Mathieu Rubeaux, Tobias Fuchs, Leandro Slipczuk, Guido Germano, Damini Dey, Daniel Berman, Philipp Kaufmann, Piotr Slomka, "Automatic valve plane localization in myocardial perfusion SPECT images using machine learning." In the proceedings of Journal of Nuclear Medicine, 2016.
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Cardiac motion compensation improves reproducibility of 18F-sodium fluoride PET uptake quantification in the aortic valve
Mathieu Rubeaux, Tania Pawade, Tim Cartlidge, Yuka Otaki, Marc Dweck, Damini Dey, Guido Germano, David Newby, Daniel Berman, Piotr Slomka, "Cardiac motion compensation improves reproducibility of 18F-sodium fluoride PET uptake quantification in the aortic valve." In the proceedings of Journal of Nuclear Medicine, 2016.
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Epicardial adipose tissue volume but not density is an independent predictor for myocardial ischemia
Michaela Hell, Xiaowei Ding, Mathieu Rubeaux, Piotr Slomka, Heidi Gransar, Demetri Terzopoulos, Sean Hayes, Mohamed Marwan, Stephan Achenbach, Daniel Berman, "Epicardial adipose tissue volume but not density is an independent predictor for myocardial ischemia." Journal of cardiovascular computed tomography, 2016.
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Motion Correction of 18F-NaF PET for Imaging Coronary Atherosclerotic Plaques
Mathieu Rubeaux, Nikhil Joshi, Marc Dweck, Alison Fletcher, Manish Motwani, Louise Thomson, Guido Germano, Damini Dey, Debiao Li, Daniel Berman, David Newby, Piotr Slomka, "Motion Correction of 18-F-NaF PET for Imaging Coronary Atherosclerotic Plaques." Journal of Nuclear Medicine, 2016.
Quantitation of left ventricular ejection fraction reserve from early gated regadenoson stress Tc-99m high-efficiency SPECT
Yafim Brodov, Mathews Fish, Mathieu Rubeaux, Yuka Otaki, Heidi Gransar, Mark Lemley, Jim Gerlach, Daniel Berman, Guido Germano, Piotr Slomka, "Quantitation of left ventricular ejection fraction reserve from early gated regadenoson stress Tc-99m high-efficiency SPECT." Journal of Nuclear Cardiology, 2016.
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Automatic detection of cardiovascular risk in CT attenuation correction maps in Rb-82 PET/CTs
Ivana Išgum, Bob De, Jelmer Wolterink, Damini Dey, Daniel Berman, Mathieu Rubeaux, Tim Leiner, Piotr Slomka, "Automatic detection of cardiovascular risk in CT attenuation correction maps in Rb-82 PET/CTs." In the proceedings of SPIE Medical Imaging, 2016.
Demons versus level-set motion registration for coronary 18F-sodium fluoride PET
Mathieu Rubeaux, Nikhil Joshi, Marc Dweck, Alison Fletcher, Manish Motwani, Louise Thomson, Guido Germano, Damini Dey, Daniel Berman, David Newby, Piotr Slomka, "Demons versus level-set motion registration for coronary 18F-sodium fluoride PET." In the proceedings of SPIE Medical Imaging, 2016.
Normal Databases for the Relative Quantification of Myocardial Perfusion
Mathieu Rubeaux, Yuan Xu, Guido Germano, Daniel Berman, Piotr Slomka, "Normal Databases for the Relative Quantification of Myocardial Perfusion." Current Cardiovascular Imaging Reports, 2016.
Automatic Valve Plane Localization in Myocardial Perfusion SPECT/CT by Machine Learning: Anatomic and Clinical Validation
Julian Betancur, Mathieu Rubeaux, Tobias Fuchs, Yuka Otaki, Yoav Arnson, Leandro Slipczuk, Dominik Benz, Guido Germano, Damini Dey, Chih-Jen Lin, "Automatic Valve Plane Localization in Myocardial Perfusion SPECT/CT by Machine Learning: Anatomic and Clinical Validation." Journal of Nuclear Medicine, 2017.
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Automatic determination of cardiovascular risk by CT attenuation correction maps in Rb-82 PET/CT
Ivana Išgum, Bob Vos, Jelmer Wolterink, Damini Dey, Daniel Berman, Mathieu Rubeaux, Tim Leiner, Piotr Slomka, "Automatic determination of cardiovascular risk by CT attenuation correction maps in Rb-82 PET/CT." Journal of Nuclear Cardiology, 2017.
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Enhancing Cardiac PET by Motion Correction Techniques
Mathieu Rubeaux, Mhairi Doris, Adam Alessio, Piotr Slomka, "Enhancing Cardiac PET by Motion Correction Techniques." Current cardiology reports, 2017.
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Molecular Imaging of Vulnerable Coronary Plaque: A Pathophysiologic Perspective
Sandeep Krishnan, Yuka Otaki, Mhairi Doris, Leandro Slipczuk, Yoav Arnson, Mathieu Rubeaux, Damini Dey, Piotr Slomka, Daniel Berman, Balaji Tamarappoo, "Molecular Imaging of Vulnerable Coronary Plaque: A Pathophysiologic Perspective." Journal of Nuclear Medicine, 2017.
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Motion-corrected imaging of the aortic valve with 18F-NaF PET/CT and PET/MR: a feasibility study
Mhairi Doris, Mathieu Rubeaux, Tania Pawade, Yuka Otaki, Yibin Xie, Debiao Li, Balaji Tamarappoo, David Newby, Daniel Berman, Marc Dweck, "Motion-corrected imaging of the aortic valve with 18F-NaF PET/CT and PET/MR: a feasibility study." Journal of Nuclear Medicine, 2017.
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Motion correction for imaging small lesions in coronary positron emission tomography gated images: a phantom study
Mathieu Rubeaux, Adam Alessio, Mhairi Doris, Marc Dweck, David Newby, Damini Dey, Daniel Berman, Piotr Slomka, "Motion correction for imaging small lesions in coronary positron emission tomography gated images: a phantom study." In the proceedings of Journal of Nuclear Medicine, 2017.
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Technical consideration for dual ECG/respiratory-gated cardiac PET imaging
Mark Hyun, Jim Gerlach, Mathieu Rubeaux, Piotr Slomka, "Technical consideration for dual ECG/respiratory-gated cardiac PET imaging." Journal of Nuclear Cardiology, 2017.
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Quantification with normal limits: New cameras and low-dose imaging
Piotr Slomka, Mathieu Rubeaux, Guido Germano, "Quantification with normal limits: New cameras and low-dose imaging." Journal of Nuclear Cardiology, 2017.
Optimization of Reconstruction and Quantification for Motion-Corrected Coronary 18F-NaF PET
Mhairi Doris, Mathieu Rubeaux, Sebastien Cadet, Yuka Otaki, Damini Dey, Marc Dweck, David Newby, Daniel Berman, Piotr Slomka, "Optimization of Reconstruction and Quantification for Motion-Corrected Coronary 18F-NaF PET." In the proceedings of Circulation, 2018.
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Active Organs Segmentation in Metastatic Breast Cancer Images combining Superpixels and Deep Learning Methods
Constance Fourcade, Gianmarco Santini, Ludovic Ferrer, Caroline Rousseau, Mathilde Colombie, Mario Campone, Mathieu Rubeaux, Diana Mateus, "Active Organs Segmentation in Metastatic Breast Cancer Images combining Superpixels and Deep Learning Methods." In the proceedings of Nuclear Technologies for Health Symposium, 2020.
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Comparison between traditional and deep learning-based semi-automatic segmentation methods for metastatic breast cancer lesions monitoring
Noémie Moreau, Caroline Rousseau, Ludovic Ferrer, Mario Campone, Mathilde Colombie, Nicolas Normand, Mathieu Rubeaux, "Comparison between traditional and deep learning-based semi-automatic segmentation methods for metastatic breast cancer lesions monitoring." In the proceedings of Nuclear Technologies for Health Symposium, 2020.
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Segmentation automatique des métastases hépatiques en imagerie TEP/TDM basée sur l’apprentissage profond dans le cadre du cancer du sein métastatique
G. Santini, C. Fourcade, C. Rousseau, L. Ferrer, M. Campone, M. Colombié, M. Rubeaux, "Segmentation automatique des métastases hépatiques en imagerie TEP/TDM basée sur l’apprentissage profond dans le cadre du cancer du sein métastatique." In the proceedings of Médecine Nucléaire, 2020.
Optimization of reconstruction and quantification of motion-corrected coronary PET-CT
Mhairi Doris, Yuka Otaki, Sandeep Krishnan, Jacek Kwiecinski, Mathieu Rubeaux, Adam Alessio, Tinsu Pan, Sebastien Cadet, Damini Dey, Marc Dweck, David Newby, Daniel Berman, Piotr Slomka, "Optimization of reconstruction and quantification of motion-corrected coronary PET-CT." Journal of Nuclear Cardiology, 2020.
Combining Superpixels and Deep Learning Approaches to Segment Active Organs in Metastatic Breast Cancer PET Images
Constance Fourcade, Ludovic Ferrer, Gianmarco Santini, Noemie Moreau, Caroline Rousseau, Marie Lacombe, Camille Guillerminet, Mathilde Colombie, Mario Campone, Diana Mateus, Mathieu Rubeaux, "Combining Superpixels and Deep Learning Approaches to Segment Active Organs in Metastatic Breast Cancer PET Images." In the proceedings of 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2020.
Deep learning approaches for bone and bone lesion segmentation on 18FDG PET/CT imaging in the context of metastatic breast cancer
Noemie Moreau, Caroline Rousseau, Constance Fourcade, Gianmarco Santini, Ludovic Ferrer, Marie Lacombe, Camille Guillerminet, Mario Campone, Mathilde Colombie, Mathieu Rubeaux, {And} Normand, "Deep learning approaches for bone and bone lesion segmentation on 18FDG PET/CT imaging in the context of metastatic breast cancer." In the proceedings of 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2020.
Unpaired PET/CT image synthesis of liver region using CycleGAN
Gianmarco Santini, Constance Fourcade, Noémie Moreau, Caroline Rousseau, Ludovic Ferrer, Marie Lacombe, Vincent Fleury, Mario Campone, Pascal Jézéquel, Mathieu Rubeaux, "Unpaired PET/CT image synthesis of liver region using CycleGAN." In the proceedings of 16th International Symposium on Medical Information Processing and Analysis, 2020.
Using Elastix to Register Inhale/Exhale Intrasubject Thorax CT: An Unsupervised Baseline to the Task 2 of the Learn2Reg Challenge
Constance Fourcade, Mathieu Rubeaux, Diana Mateus, "Using Elastix to Register Inhale/Exhale Intrasubject Thorax CT: An Unsupervised Baseline to the Task 2 of the Learn2Reg Challenge." In the proceedings of Segmentation, Classification, and Registration of Multi-modality Medical Imaging Data, 2021.
Series Title: Lecture Notes in Computer Science
Automatic classification of benign and malignant kidney masses using radiomics. A retrospective study exploiting the KiTS19 dataset
Gianmarco Santini, Yvon Nzoughet, Constance Fourcade, Noémie Moreau, Mathieu Rubeaux, "Automatic classification of benign and malignant kidney masses using radiomics. A retrospective study exploiting the KiTS19 dataset." In the proceedings of Medical Imaging 2021: Image Processing, 2021.
Comparison between threshold-based and deep learning-based bone segmentation on whole-body CT images
Noémie Moreau, Caroline Rousseau, Constance Fourcade, Gianmarco Santini, Ludovic Ferrer, Marie Lacombe, Camille Guillerminet, Pascal Jezequel, Mario Campone, Nicolas Normand, Mathieu Rubeaux, "Comparison between threshold-based and deep learning-based bone segmentation on whole-body CT images." In the proceedings of SPIE Medical Imaging, 2021.
Quantification automatique de l’activité de fond pour le calcul du critère PERCIST (+ Running poster)
G. Santini, N. Moreau, C. Fourcade, C. Rousseau, L. Ferrer, M. Campone, M. Colombié, P. Jézéquel, M. Rubeaux, "Quantification automatique de l’activité de fond pour le calcul du critère PERCIST (+ Running poster)." In the proceedings of Médecine Nucléaire, 2021.
Automatic Segmentation of Metastatic Breast Cancer Lesions on 18F-FDG PET/CT Longitudinal Acquisitions for Treatment Response Assessment
Noémie Moreau, Caroline Rousseau, Constance Fourcade, Gianmarco Santini, Aislinn Brennan, Ludovic Ferrer, Marie Lacombe, Camille Guillerminet, Mathilde Colombié, Pascal Jézéquel, Mario Campone, Nicolas Normand, Mathieu Rubeaux, "Automatic Segmentation of Metastatic Breast Cancer Lesions on 18F-FDG PET/CT Longitudinal Acquisitions for Treatment Response Assessment." Cancers, 2021.
The EPICURE study: a pilot prospective cohort study of heterogeneous and massive data integration in metastatic breast cancer patients
Mathilde Colombié, Pascal Jézéquel, Mathieu Rubeaux, Jean-Sébastien Frenel, Frédéric Bigot, Valérie Seegers, Mario Campone, "The EPICURE study: a pilot prospective cohort study of heterogeneous and massive data integration in metastatic breast cancer patients." BMC Cancer, 2021.
Feasibility of creation of a clinico-biological database: A prospective longitudinal cohort study of metastatic breast cancer patients (epicuresein)
Mathilde Colombié, Pascal Jézéquel, Mathieu Rubeaux, Jean-Sebastien Frenel, Frédéric Bigot, Valérie Seegers, Mario Campone, "Feasibility of creation of a clinico-biological database: A prospective longitudinal cohort study of metastatic breast cancer patients (epicuresein)." In the proceedings of Cancer Research, 2022.
PERCIST-like response assessment with FDG PET based on automatic segmentation of all lesions in metastatic breast cancer.
Constance Fourcade, Jean-Sebastien Frenel, Noémie Moreau, Gianmarco Santini, Aislinn Brennan, Caroline Rousseau, Marie Lacombe, Vincent Fleury, Mathilde Colombié, Pascal Jézéquel, Bruno Maucherat, Mario Campone, Diana Mateus, Ludovic Ferrer, Mathieu Rubeaux, "PERCIST-like response assessment with FDG PET based on automatic segmentation of all lesions in metastatic breast cancer.." In the proceedings of Journal of Clinical Oncology, 2022.
Influence of inputs for bone lesion segmentation in longitudinal$^textrm18$ F-FDG PET/CT imaging studies
Noemie Moreau, Caroline Rousseau, Constance Fourcade, Gianmarco Santini, Ludovic Ferrer, Marie Lacombe, Camille Guillerminet, Mathilde Colombie, Pascal Jezequel, Mario Campone, Mathieu Rubeaux, Nicolas Normand, "Influence of inputs for bone lesion segmentation in longitudinal 18F-FDG PET/CT imaging studies." In the proceedings of 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2022.
Deformable image registration with deep network priors: a study on longitudinal PET images
Constance Fourcade, Ludovic Ferrer, Noémie Moreau, Gianmarco Santini, Aislinn Brennan, Caroline Rousseau, Marie Lacombe, Vincent Fleury, Mathilde Colombié, Pascal Jézéquel, Mathieu Rubeaux, Diana Mateus, "Deformable image registration with deep network priors: a study on longitudinal PET images." Physics in Medicine & Biology, 2022.
Learn2Reg: Comprehensive Multi-Task Medical Image Registration Challenge, Dataset and Evaluation in the Era of Deep Learning
Alessa Hering, Lasse Hansen, Tony Mok, Albert Chung, Hanna Siebert, Stephanie Hager, Annkristin Lange, Sven Kuckertz, Stefan Heldmann, Wei Shao, Sulaiman Vesal, Mirabela Rusu, Geoffrey Sonn, Theo Estienne, Maria Vakalopoulou, Luyi Han, Yunzhi Huang, Pew-Thian Yap, Mikael Brudfors, Yael Balbastre, Samuel Joutard, Marc Modat, Gal Lifshitz, Dan Raviv, Jinxin Lv, Qiang Li, Vincent Jaouen, Dimitris Visvikis, Constance Fourcade, Mathieu Rubeaux, Wentao Pan, Zhe Xu, Bailiang Jian, Francesca De, Marek Wodzinski, Niklas Gunnarsson, Jens Sjolund, Daniel Grzech, Huaqi Qiu, Zeju Li, Alexander Thorley, Jinming Duan, Christoph Grosbrohmer, Andrew Hoopes, Ingerid Reinertsen, Yiming Xiao, Bennett Landman, Yuankai Huo, Keelin Murphy, Nikolas Lessmann, Bram Van, Adrian Dalca, Mattias Heinrich, "Learn2Reg: Comprehensive Multi-Task Medical Image Registration Challenge, Dataset and Evaluation in the Era of Deep Learning." IEEE Transactions on Medical Imaging, 2023.
Predicting recurrence in head and neck cancer using new threshold vs feature behavior curves from 18FFDG PET/CT images
Eliana Villa, Oscar Acosta, Xavier Palard-Novello, Renaud De, Joël Castelli, Isabella Cuberos, Mathieu Rubeaux, "Predicting recurrence in head and neck cancer using new threshold vs feature behavior curves from 18FFDG PET/CT images." In the proceedings of Radiotherapy and Oncology, 2025.
Inclusion of ipsilateral salivary gland PET/CT features improves xerostomia prediction after radiotherapy in head and neck cancer
Luis Torres, Santiago Osorio-Botero, Xavier Palard, Renaud De, Lucía Cubero, Oscar Acosta, Joel Castelli, Mathieu Rubeaux, "Inclusion of ipsilateral salivary gland PET/CT features improves xerostomia prediction after radiotherapy in head and neck cancer." In the proceedings of ESTRO, 2026.
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talks
Talk 1 on Relevant Topic in Your Field
This is a description of your talk, which is a markdown file that can be all markdown-ified like any other post. Yay markdown!
Conference Proceeding talk 3 on Relevant Topic in Your Field
This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
teaching
Undergraduate Students - Data science
Licence 2 ISTN, Université de Rennes, ISTIC, 2025
Data Science for undergraduate students :
- Probabilities :
- random variables
- mean and variance
- discrete and continuous probability laws
- law of large numbers and central limit theorem
- Statistics :
- sampling
- estimation and confidence intervals
- hypothesis tests
Military personnel - Python Programming
School of of Transmissions, Digital and Cyber, Université de Rennes, ISTIC, 2025
Basic Python programming courses for military personnel undergoing retraining to become cybersecurity technicians. They are part of the School of of Transmissions, Digital and Cyber.
Undergraduate Students - Information Theory
Licence 1 ISTN, Université de Rennes, ISTIC, 2025
Information Theory for undergraduate students :
- number representation
- numbering system
- coding, compression (Shannon-Fano, Huffman)
- error correcting codes
Undergraduate Students - Probabilities & Statistics
Licence 2 ISTN, Université de Rennes, ISTIC, 2025
Probabilities and Statistics for undergraduate students :
- Probabilities :
- random variables
- mean and variance
- discrete and continuous probability laws
- law of large numbers and central limit theorem
- Statistics :
- sampling
- estimation and confidence intervals
- hypothesis tests
Undergraduate Students - Unplugged Artificial Intelligence
Licence 1 ISTN, Université de Rennes, ISTIC, 2025
Unplugged Artificial Intelligence. We collectively set-up this collection of practical work for 1st year student to discover Artificial Intelligence through Unplugged (without computer) activities. I personnaly conceived 2 modules with my colleague Myriam Bontonou :
- Planning & graphs paths
- Markov Fields
Graduate Students - Artificial Intelligence & Design
Master 1 IA, Université de Rennes, ISTIC, 2026
We set-up a collaborative project between the Master 1 “Artificial Intelligence” and a school of design from Rennes (DSAA - Diplôme Supérieur d’Arts Appliqués de Rennes). The students of the 2 schools are thus able to collaborate on projects at the interface between design and artificial intelligence using public data from the Rennes metropolitan area.
Graduate Students - Artificial Intelligence based Computer Vision
Master 2 IA, Université de Rennes, ISTIC, 2026
Artificial Intelligence based Computer Vision A set of lectures and practical work on Artificial Intelligence applied to computer vision :
- computer vision before AI
- Convolutional Neural Networks for computer vision
- Reference networks in computer vision