Mathieu Hatt

Orcid: 0000-0002-8938-8667

According to our database1, Mathieu Hatt authored at least 32 papers between 2006 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Online presence:

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Bibliography

2025
Advancing chest X-ray diagnostics: A novel CycleGAN-based preprocessing approach for enhanced lung disease classification in ChestX-Ray14.
Comput. Methods Programs Biomed., 2025

2024
A Systematic Review: Classification of Lung Diseases from Chest X-Ray Images Using Deep Learning Algorithms.
SN Comput. Sci., April, 2024

2023
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., December, 2023

MedShapeNet - A Large-Scale Dataset of 3D Medical Shapes for Computer Vision.
CoRR, 2023

2022
Head and neck tumor segmentation in PET/CT: The HECKTOR challenge.
Medical Image Anal., 2022

Joint nnU-Net and Radiomics Approaches for Segmentation and Prognosis of Head and Neck Cancers with PET/CT Images.
Proceedings of the Head and Neck Tumor Segmentation and Outcome Prediction, 2022


Evaluation of Importance Estimators in Deep Learning Classifiers for Computed Tomography.
Proceedings of the Explainable and Transparent AI and Multi-Agent Systems, 2022

2021
Overview of the HECKTOR Challenge at MICCAI 2021: Automatic Head and Neck Tumor Segmentation and Outcome Prediction in PET/CT Images.
Proceedings of the Head and Neck Tumor Segmentation and Outcome Prediction, 2021

2020
Squeeze-and-Excitation Normalization for Automated Delineation of Head and Neck Primary Tumors in Combined PET and CT Images.
Proceedings of the Head and Neck Tumor Segmentation - First Challenge, 2020

Squeeze-and-Excitation Normalization for Brain Tumor Segmentation.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2020

2019
Image Enhancement With PDEs and Nonconservative Advection Flow Fields.
IEEE Trans. Image Process., 2019

Next Generation Radiogenomics Sequencing for Prediction of EGFR and KRAS Mutation Status in NSCLC Patients Using Multimodal Imaging and Machine Learning Approaches.
CoRR, 2019

PET/CT Radiomic Sequencer for Prediction of EGFR and KRAS Mutation Status in NSCLC Patients.
CoRR, 2019

Encoder-Decoder Network for Brain Tumor Segmentation on Multi-sequence MRI.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2019

2018
The first MICCAI challenge on PET tumor segmentation.
Medical Image Anal., 2018

Image Filtering with Advectors.
Proceedings of the 2018 IEEE International Conference on Image Processing, 2018

2016
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, 2016

Prognosis classification in glioblastoma multiforme using multimodal MRI derived heterogeneity textural features: impact of pre-processing choices.
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, 2016

2015
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., 2015

Prognostic value of multimodal MRI tumor features in Glioblastoma multiforme using textural features analysis.
Proceedings of the 12th IEEE International Symposium on Biomedical Imaging, 2015

2013
Denoising of PET images by combining wavelets and curvelets for improved preservation of resolution and quantitation.
Medical Image Anal., 2013

2012
Image Change Detection Using Paradoxical Theory for Patient Follow-Up Quantitation and Therapy Assessment.
IEEE Trans. Medical Imaging, 2012

Multi modal images analysis and processing in oncology. (Analyse et traitement d'images multi modales en oncologie).
, 2012

2009
A Fuzzy Locally Adaptive Bayesian Segmentation Approach for Volume Determination in PET.
IEEE Trans. Medical Imaging, 2009

Incorporating Patient-Specific Variability in the Simulation of Realistic Whole-Body <sup>18</sup>hboxF-FDG Distributions for Oncology Applications.
Proc. IEEE, 2009

2008
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).
PhD thesis, 2008

Contrast enhancement in emission tomography by way of synergistic PET/CT image combination.
Comput. Methods Programs Biomed., 2008

Conditional partial volume correction for emission tomography: A wavelet-based hidden Markov model and multi-resolution approach.
Proceedings of the 2008 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2008

2007
Non-stationary fuzzy Markov chain.
Pattern Recognit. Lett., 2007

3d Fuzzy Adaptive Unsupervised Bayesian Segmentation for Volume Determination in Pet.
Proceedings of the 2007 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2007

2006
Fuzzy versus hard hidden Markov chains segmentation for volume determination and quantitation in noisy PET images.
Proceedings of the 2006 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2006


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