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Mathieu Hatt
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2020 – today
- 2025
- [j13]Aya Hage Chehade, Nassib Abdallah, Jean-Marie Marion, Mathieu Hatt, Mohamad Oueidat, Pierre Chauvet:
Advancing chest X-ray diagnostics: A novel CycleGAN-based preprocessing approach for enhanced lung disease classification in ChestX-Ray14. Comput. Methods Programs Biomed. 259: 108518 (2025) - 2024
- [j12]Aya Hage Chehade
, Nassib Abdallah, Jean-Marie Marion, Mathieu Hatt
A Systematic Review: Classification of Lung Diseases from Chest X-Ray Images Using Deep Learning Algorithms. SN Comput. Sci. 5(4): 405 (2024) - 2023
- [j11]Vincent Andrearczyk, Valentin Oreiller, Sarah Boughdad, Catherine Cheze Le Rest, Olena Tankyevych, Hesham Elhalawani
Automatic Head and Neck Tumor segmentation and outcome prediction relying on FDG-PET/CT images: Findings from the second edition of the HECKTOR challenge. Medical Image Anal. 90: 102972 (2023) - [e2]Vincent Andrearczyk
Head and Neck Tumor Segmentation and Outcome Prediction - Third Challenge, HECKTOR 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings. Lecture Notes in Computer Science 13626, Springer 2023, ISBN 978-3-031-27419-0 [contents] - [i8]Jianning Li, Antonio Pepe, Christina Gsaxner, Gijs Luijten, Yuan Jin, Narmada Ambigapathy, Enrico Nasca, Naida Solak, Gian Marco Melito
MedShapeNet - A Large-Scale Dataset of 3D Medical Shapes for Computer Vision. CoRR abs/2308.16139 (2023) - 2022
- [j10]Valentin Oreiller, Vincent Andrearczyk, Mario Jreige
Head and neck tumor segmentation in PET/CT: The HECKTOR challenge. Medical Image Anal. 77: 102336 (2022) - [c13]Lennart Brocki, Wistan Marchadour, Jonas Maison
Evaluation of Importance Estimators in Deep Learning Classifiers for Computed Tomography. EXTRAAMAS@AAMAS 2022: 3-18 - [c12]Vincent Andrearczyk, Valentin Oreiller, Moamen Abobakr
Overview of the HECKTOR Challenge at MICCAI 2022: Automatic Head and Neck Tumor Segmentation and Outcome Prediction in PET/CT. HECKTOR@MICCAI 2022: 1-30 - [c11]Hui Xu, Yihao Li, Wei Zhao, Gwenolé Quellec
Joint nnU-Net and Radiomics Approaches for Segmentation and Prognosis of Head and Neck Cancers with PET/CT Images. HECKTOR@MICCAI 2022: 154-165 - [e1]Vincent Andrearczyk
Head and Neck Tumor Segmentation and Outcome Prediction - Second Challenge, HECKTOR 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, Proceedings. Lecture Notes in Computer Science 13209, Springer 2022, ISBN 978-3-030-98252-2 [contents] - [i7]Vincent Andrearczyk, Valentin Oreiller, Sarah Boughdad, Catherine Cheze Le Rest, Hesham Elhalawani, Mario Jreige, John O. Prior, Martin Vallières, Dimitris Visvikis, Mathieu Hatt, Adrien Depeursinge:
Overview of the HECKTOR Challenge at MICCAI 2021: Automatic Head and Neck Tumor Segmentation and Outcome Prediction in PET/CT Images. CoRR abs/2201.04138 (2022) - [i6]Lennart Brocki, Wistan Marchadour, Jonas Maison, Bogdan Badic, Panagiotis G. Papadimitroulas, Mathieu Hatt, Franck Vermet, Neo Christopher Chung
Evaluation of importance estimators in deep learning classifiers for Computed Tomography. CoRR abs/2209.15398 (2022) - [i5]Hui Xu, Yihao Li, Wei Zhao, Gwenolé Quellec, Lijun Lu, Mathieu Hatt:
Joint nnU-Net and Radiomics Approaches for Segmentation and Prognosis of Head and Neck Cancers with PET/CT images. CoRR abs/2211.10138 (2022) - 2021
- [c10]Vincent Andrearczyk, Valentin Oreiller, Sarah Boughdad, Catherine Cheze Le Rest, Hesham Elhalawani
Overview of the HECKTOR Challenge at MICCAI 2021: Automatic Head and Neck Tumor Segmentation and Outcome Prediction in PET/CT Images. HECKTOR@MICCAI 2021: 1-37 - [i4]Andrei Iantsen, Dimitris Visvikis, Mathieu Hatt:
Squeeze-and-Excitation Normalization for Automated Delineation of Head and Neck Primary Tumors in Combined PET and CT Images. CoRR abs/2102.10446 (2021) - 2020
- [c9]Andrei Iantsen, Vincent Jaouen, Dimitris Visvikis, Mathieu Hatt
Squeeze-and-Excitation Normalization for Brain Tumor Segmentation. BrainLes@MICCAI (2) 2020: 366-373 - [c8]Andrei Iantsen
Squeeze-and-Excitation Normalization for Automated Delineation of Head and Neck Primary Tumors in Combined PET and CT Images. HECKTOR@MICCAI 2020: 37-43
2010 – 2019
- 2019
- [j9]Vincent Jaouen
Image Enhancement With PDEs and Nonconservative Advection Flow Fields. IEEE Trans. Image Process. 28(6): 3075-3088 (2019) - [c7]Andrei Iantsen, Vincent Jaouen, Dimitris Visvikis, Mathieu Hatt
Encoder-Decoder Network for Brain Tumor Segmentation on Multi-sequence MRI. BrainLes@MICCAI (2) 2019: 296-302 - [i3]Isaac Shiri, Hassan Maleki, Ghasem Hajianfar, Hamid Abdollahi, Saeed Ashrafinia, Mathieu Hatt, Mehrdad Oveisi, Arman Rahmim:
PET/CT Radiomic Sequencer for Prediction of EGFR and KRAS Mutation Status in NSCLC Patients. CoRR abs/1906.06623 (2019) - [i2]Isaac Shiri, Hassan Maleki, Ghasem Hajianfar, Hamid Abdollahi, Saeed Ashrafinia, Mathieu Hatt, Mehrdad Oveisi, Arman Rahmim:
Next Generation Radiogenomics Sequencing for Prediction of EGFR and KRAS Mutation Status in NSCLC Patients Using Multimodal Imaging and Machine Learning Approaches. CoRR abs/1907.02121 (2019) - 2018
- [j8]Mathieu Hatt, Baptiste Laurent, Anouar Ouahabi, Hadi Fayad
The first MICCAI challenge on PET tumor segmentation. Medical Image Anal. 44: 177-195 (2018) - [c6]Vincent Jaouen, Laurent Gaubert
Image Filtering with Advectors. ICIP 2018: 1513-1517 - 2016
- [c5]Taman Upadhaya, Yannick Morvan, Eric Stindel, Pierre-Jean Le Reste, Mathieu Hatt:
Prognosis classification in glioblastoma multiforme using multimodal MRI derived heterogeneity textural features: impact of pre-processing choices. Computer-Aided Diagnosis 2016: 97850W - [i1]Marie-Charlotte Desseroit, Florent Tixier, Wolfgang Weber, Barry A. Siegel, Catherine Cheze Le Rest, Dimitris Visvikis, Mathieu Hatt:
Reliability of PET/CT shape and heterogeneity features in functional and morphological components of Non-Small Cell Lung Cancer tumors: a repeatability analysis in a prospective multi-center cohort. CoRR abs/1610.01390 (2016) - 2015
- [j7]Mathieu Hatt, Dimitris Visvikis
Regarding "Segmentation of heterogeneous or small FDG PET positive tissue based on a 3D-locally adaptive random walk algorithm" By DP. Onoma et al. Comput. Medical Imaging Graph. 46: 300-301 (2015) - [c4]Taman Upadhaya, Yannick Morvan, Eric Stindel, Pierre-Jean Le Reste
Prognostic value of multimodal MRI tumor features in Glioblastoma multiforme using textural features analysis. ISBI 2015: 50-54 - 2013
- [j6]Adrien Le Pogam, H. Hanzouli, Mathieu Hatt, Catherine Cheze Le Rest, Dimitris Visvikis
Denoising of PET images by combining wavelets and curvelets for improved preservation of resolution and quantitation. Medical Image Anal. 17(8): 877-891 (2013) - 2012
- [b2]Mathieu Hatt:
Multi modal images analysis and processing in oncology. (Analyse et traitement d'images multi modales en oncologie). University of Western Brittany, Brest, France, 2012 - [j5]Simon David, Dimitris Visvikis
Image Change Detection Using Paradoxical Theory for Patient Follow-Up Quantitation and Therapy Assessment. IEEE Trans. Medical Imaging 31(9): 1743-1753 (2012)
2000 – 2009
- 2009
- [j4]Amandine Le Maitre, William Paul Segars, Simon Marache, Anthonin Reilhac
Incorporating Patient-Specific Variability in the Simulation of Realistic Whole-Body 18hboxF-FDG Distributions for Oncology Applications. Proc. IEEE 97(12): 2026-2038 (2009) - [j3]Mathieu Hatt, Catherine Cheze Le Rest, Alexandre Turzo, Christian Roux, Dimitris Visvikis
A Fuzzy Locally Adaptive Bayesian Segmentation Approach for Volume Determination in PET. IEEE Trans. Medical Imaging 28(6): 881-893 (2009) - 2008
- [b1]Mathieu Hatt:
Détermination automatique des volumes fonctionnels en imagerie d'émission pour les applications en oncologie. (Automatic delineation of functional volumes in emission tomography for oncology applications). University of Western Brittany, Brest, France, 2008 - [j2]Nicolas Boussion, Mathieu Hatt, Frédéric Lamare
Contrast enhancement in emission tomography by way of synergistic PET/CT image combination. Comput. Methods Programs Biomed. 90(3): 191-201 (2008) - [c3]Adrien Le Pogam, Mathieu Hatt, Nicolas Boussion, Denis Guilloteau, Jean-Louis Baulieu, Caroline Prunier, Federico E. Turkheimer
Conditional partial volume correction for emission tomography: A wavelet-based hidden Markov model and multi-resolution approach. ISBI 2008: 1319-1322 - 2007
- [j1]Fabien Salzenstein, Christophe Collet, Steven Le Cam, Mathieu Hatt:
Non-stationary fuzzy Markov chain. Pattern Recognit. Lett. 28(16): 2201-2208 (2007) - [c2]Mathieu Hatt, Christian Roux, Dimitris Visvikis:
3d Fuzzy Adaptive Unsupervised Bayesian Segmentation for Volume Determination in Pet. ISBI 2007: 328-331 - 2006
- [c1]Mathieu Hatt, Nicolas Boussion, Frédéric Lamare, Christophe Collet, Fabien Salzenstein, Christian Roux, Yves Bizais, Catherine Cheze Le Rest, Dimitris Visvikis:
Fuzzy versus hard hidden Markov chains segmentation for volume determination and quantitation in noisy PET images. ISBI 2006: 1376-1379
Coauthor Index
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