Dr. Mathieu Rubeaux Profile

Dr. Mathieu Rubeaux

Project Leader at KEOSYS

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Publications (7)

Proceedings Article | 15 February 2021 Poster + Presentation + Paper

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

Proceedings Volume 11597, 115972U (2021) https://doi.org/10.1117/12.2580892

KEYWORDS: Image segmentation, Bone, Computed tomography, Visualization, Heart

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Proceedings Article | 15 February 2021 Poster + Presentation + Paper

Automatic classification of benign and malignant kidney masses using radiomics. A retrospective study exploiting the KiTS19 dataset

Gianmarco Santini, Yvon Nzoughet Obame, Constance Fourcade, Noémie Moreau, Mathieu Rubeaux

Proceedings Volume 11596, 115962K (2021) https://doi.org/10.1117/12.2579901

KEYWORDS: Kidney, Tumors, Tumor growth modeling, Tissues, Neural networks, Feature selection, Feature extraction, Convolutional neural networks

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Proceedings Article | 3 November 2020 Paper

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

Proceedings Volume 11583, 115830T (2020) https://doi.org/10.1117/12.2576095

KEYWORDS: Liver, Data modeling, Medical imaging, Image processing

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Proceedings Article | 21 March 2016 Paper

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

Proceedings Volume 9784, 97843Y (2016) https://doi.org/10.1117/12.2217179

KEYWORDS: Positron emission tomography, Image registration, Image quality, Arteries, Angiography, Electrocardiography, Image processing, Heart, Statistical analysis, Image enhancement, Motion estimation

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Ruptured coronary atherosclerotic plaques commonly cause acute myocardial infarction. It has been recently shown that active microcalcification in the coronary arteries, one of the features that characterizes vulnerable plaques at risk of rupture, can be imaged using cardiac gated ¹⁸F-sodium fluoride (¹⁸F-NaF) PET. We have shown in previous work that a motion correction technique applied to cardiac-gated ¹⁸F-NaF PET images can enhance image quality and improve uptake estimates. In this study, we further investigated the applicability of different algorithms for registration of the coronary artery PET images. In particular, we aimed to compare demons vs. level-set nonlinear registration techniques applied for the correction of cardiac motion in coronary ¹⁸F-NaF PET. To this end, fifteen patients underwent ¹⁸F-NaF PET and prospective coronary CT angiography (CCTA). PET data were reconstructed in 10 ECG gated bins; subsequently these gated bins were registered using demons and level-set methods guided by the extracted coronary arteries from CCTA, to eliminate the effect of cardiac motion on PET images. Noise levels, target-to-background ratios (TBR) and global motion were compared to assess image quality. Compared to the reference standard of using only diastolic PET image (25% of the counts from PET acquisition), cardiac motion registration using either level-set or demons techniques almost halved image noise due to the use of counts from the full PET acquisition and increased TBR difference between ¹⁸F-NaF positive and negative lesions. The demons method produces smoother deformation fields, exhibiting no singularities (which reflects how physically plausible the registration deformation is), as compared to the level-set method, which presents between 4 and 8% of singularities, depending on the coronary artery considered. In conclusion, the demons method produces smoother motion fields as compared to the level-set method, with a motion that is physiologically plausible. Therefore, level-set technique will likely require additional post-processing steps. On the other hand, the observed TBR increases were the highest for the level-set technique. Further investigations of the optimal registration technique of this novel coronary PET imaging technique are warranted.

Proceedings Article | 21 March 2016 Paper

Automatic detection of cardiovascular risk in CT attenuation correction maps in Rb-82 PET/CTs

Ivana Išgum, Bob de Vos, Jelmer Wolterink, Damini Dey, Daniel Berman, Mathieu Rubeaux, Tim Leiner, Piotr Slomka

Proceedings Volume 9784, 978405 (2016) https://doi.org/10.1117/12.2216992

KEYWORDS: Calcium, Algorithm development, Computed tomography, Arteries, Chest, Positron emission tomography

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Proceedings Article | 29 January 2015 Paper

Thalamic volume as a biomarker for disorders of consciousness

Mathieu Rubeaux, Jamuna Jayashri Mahalingam, Francisco Gomez, Marvin Nelson, Audrey Vanhaudenhuyse, Marie-Aurélie Bruno, Olivia Gosseries, Steven Laureys, Andrea Soddu, Natasha Lepore

Proceedings Volume 9287, 92870R (2015) https://doi.org/10.1117/12.2071146

KEYWORDS: Thalamus, Consciousness, Image segmentation, Injuries, Magnetic resonance imaging, Brain, Monochromatic aberrations, Traumatic brain injury, Diagnostics, Lithium

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Proceedings Article | 8 March 2013 Paper

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 Crevoisier, Pascal Haigron

Proceedings Volume 8671, 867106 (2013) https://doi.org/10.1117/12.2004519

KEYWORDS: Image registration, Prostate, Computed tomography, Prostate cancer, Radiotherapy, Radio propagation, Image segmentation, Bone, Bladder, Visualization

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Showing 5 of 7 publications

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