PhD students
This section lists the PhD student I supervised since my arrival at the LaTIM in 2018.
Current PhD students
- Antoine De Paepe: “Motion-compensated CT reconstruction using diffusion models”; Publications: (De Paepe et al., 2025; De Paepe et al., 2025).
- Clémentine Phung-Ngoc: “Motion-compensated PET reconstruction using diffusion models”; Publications: (Phung-Ngoc et al., 2025; Phung-Ngoc et al., 2025).
- Thore Dassow: “Material Decomposition in PCCT with Diffusion Models”; Publications: (Vazia et al., 2025; Dassow et al., 2025).
- Corentin Vazia: “Une approche de la reconstruction d’images et de la décomposition de matériaux en tomodensitométrie spectrale avec régularisa- tion par modèle de diffusion”; Publications: (Vazia et al., 2025; Vazia et al., 2024; Vazia et al., 2024).
- Youness Mellak: “Deep Learning Approaches for PET Imaging: Three-Gamma PET, Positron Range Correction and Direct Reconstruction”; Publications: (missing reference). Director: Dimitris Visvikis.
Previous PhD students
- Noel Jeffrey Pinton: “Synergistic PET/CT reconstruction using deep-learning” (2024); Publications: (Pinton et al., 2025; Pinton et al., 2023; Pinton et al., 2023).
- Zhihan Wang: “Spectral computed tomographic image reconstruction using deep learning” (2024); Publications: (Wang et al., 2025; Wang et al., 2024; Wang et al., 2022).
- Venkata Sai Sundar Kandarpa: “Tomographic image reconstruction with direct neural network approaches” (2022)); Publications: (Bousse et al., 2024; Bousse et al., 2024; Kandarpa et al., 2022; Kandarpa et al., 2022; Kandarpa et al., 2021; Kandarpa et al., 2021; Kandarpa et al., 2019).
- Suxer Alfonso Garcia: “Multi-channel computed tomographic image reconstruction by exploiting structural similarities” (2022); Publications: (Perelli et al., 2022; Alfonso Garcia et al., 2021; Alfonso Garcia et al., 2021; Alfonso Garcia et al., 2020).
- Baptiste Laurent: “Deep learning based scatter and attenuation estimation in PET imaging” (2022); Publications: (Laurent et al., 2025; Laurent et al., 2023; Laurent et al., 2020); Director: Nicolas Boussion.
- Debora Giovagnoli: “Image reconstruction for three-gamma PET imaging” (2020); Publications: (Giovagnoli et al., 2021). Director: Dimitris Visvikis.
References
2025
- Solving Blind Inverse Problems: Adaptive Diffusion Models for Motion-corrected Sparse-view 4DCTIn International Conference on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2025
- Adaptive Diffusion Models for Motion-corrected Cone-beam Head CTarXiv preprint arXiv:2504.14033, 2025
- Joint Reconstruction of the Activity and the Attenuation in PET by Diffusion Posterior Sampling: a Feasibility StudyIn International Conference on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2025
- Joint Reconstruction of Activity and Attenuation in PET by Diffusion Posterior Sampling in Wavelet Coefficient SpacearXiv preprint arXiv:2505.18782, 2025
- Material Decomposition in Photon-Counting Computed Tomography with Diffusion Models: Comparative Study and Hybridization with Variational RegularizersarXiv preprint arXiv:2503.15383, 2025
- Out-of-database Diffusion Posterior Sampling for Spectral CT Material DecompositionIn International Conference on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2025
- MultiBranch Generative Models for Multichannel Imaging With an Application to PET/CT Synergistic ReconstructionIEEE Transactions on Radiation and Plasma Medical Sciences, 2025
- MHUconnect: Multi-Head U-Net Connecting All Energy Bins For Synergistic Spectral CT ReconstructionIn International Conference on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2025
- Evaluation of deep learning-based scatter correction on a long-axial field-of-view PET scannerEuropean journal of nuclear medicine and molecular imaging, 2025
2024
- Spectral CT Two-step and One-step Material Decomposition using Diffusion Posterior SamplingIn European Signal Processing Conference (EUSIPCO), 2024
- Diffusion posterior sampling for synergistic reconstruction in spectral computed tomographyIn 2024 IEEE 21st international symposium on biomedical imaging (ISBI 2024). IEEE, 2024
- Uconnect: Synergistic Spectral CT Reconstruction With U-Nets Connecting the Energy BinsIEEE Transactions on Radiation and Plasma Medical Sciences, 2024
- A Review on Low-Dose Emission Tomography Post-Reconstruction Denoising With Neural Network ApproachesIEEE Transactions on Radiation and Plasma Medical Sciences, 2024
- Systematic Review on Learning-based Spectral CTIEEE Transactions on Radiation and Plasma Medical Sciences, 2024
2023
- Joint PET/CT Reconstruction Using a Double Variational AutoencoderIn IEEE Nuclear Science Symposium, Medical Imaging Conference and Room Temperature Semiconductor Detectors Conference, 2023
- Synergistic PET/CT Reconstruction Using a Joint Generative ModelIn International Conference on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2023
- PET scatter estimation using deep learning U-Net architecturePhysics in Medicine & Biology, 2023
2022
- Synergistic Multi-Energy Reconstruction with a Deep Penalty “Connecting the Energies”In IEEE Nuclear Science Symposium, Medical Imaging Conference and Room Temperature Semiconductor Detectors Conference, 2022
- C-DenseNet: A direct neural network-based approach for Total Body PET Image ReconstructionIn IEEE Nuclear Science Symposium, Medical Imaging Conference and Room Temperature Semiconductor Detectors Conference, 2022
- LRR-CED: low-resolution reconstruction-aware convolutional encoder–decoder network for direct sparse-view CT image reconstructionPhysics in Medicine & Biology, 2022
- Multi-channel convolutional analysis operator learning for dual-energy CT reconstructionPhysics in Medicine & Biology, 2022
2021
- Deep learning based Direct Sparse-View CT Image Reconstruction with Concatenated U-NetIn IEEE Nuclear Science Symposium, Medical Imaging Conference and Room Temperature Semiconductor Detectors Conference, 2021
- DUG-RECON: A Framework for Direct Image Reconstruction using Convolutional Generative NetworksIEEE Transactions on Radiation and Plasma Medical Sciences, 2021
- Dual-Energy CT Reconstruction with Convolutional Analysis Operator LearningIn IEEE Nuclear Science Symposium, Medical Imaging Conference and Room Temperature Semiconductor Detectors Conference, 2021
- Sparse-View Joint Reconstruction and Material Decomposition for Dual-Energy Cone-Beam Computed TomographyIn International Conference on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2021
- A Pseudo-TOF Image Reconstruction Approach for Three-Gamma Small Animal ImagingIEEE Transactions on Radiation and Plasma Medical Sciences, 2021
2020
- A Coupled Image-Motion Dictionary Learning algorithm for Motion Estimation-Compensation in Cone-Beam Computed TomographyIn IEEE Nuclear Science Symposium, Medical Imaging Conference and Room Temperature Semiconductor Detectors Conference, 2020
- Deep Learning based scatter correction for PET imagingIn IEEE Nuclear Science Symposium, Medical Imaging Conference and Room Temperature Semiconductor Detectors Conference, 2020
2019
- Direct Image Reconstruction using Generative Deep Learning NetworksIn IEEE Nuclear Science Symposium, Medical Imaging Conference and Room Temperature Semiconductor Detectors Conference, 2019