Journals:
Harb, H., Taguelmimt, K., Benoit, D., Pham, C. H., Nasr, B., & Bert, J. (2026). Fast occupational upper-limb radiation dose prediction using machine learning and Monte Carlo simulation. Journal of Radiological Protection, 46(2), 021516.
Harb, H., Benoit, D., Pham, C. H., Nasr, B., & Bert, J. (2026). Fast 3D whole-body occupational dose estimation in interventional radiology using physics-informed deep learning. Radiological Physics and Technology, 1-12.
Harb, H., Benoit, D., Rannou, A., Pham, C. H., Tissot, V., Nasr, B., & Bert, J. (2026). Machine learning-based modeling of the anode heel effect in x-ray Beam Monte Carlo simulations. Physics in Medicine and Biology, 71(1), 015007.
Zhang, J., Bousse, A., Pham, C. H., Shi, K., & Bert, J. (2026). Semi-supervised learning for dose prediction in targeted radionuclide therapy : a synthetic data study. Physics in Medicine and Biology.
Harb, H., Villa, M., Benoit, D., Pham, C. H., Nasr, B., & Bert, J. (2025). Fast operating room scattered radiation calculation in x-ray guided interventions by using deep learning. Journal of Radiological Protection, 45(4), 041524.
Eddahmani, I., Napoléon, T., Pham, C. H., Badoc, I., & El-Bouz, M. (2025). Towards automation of warehouse management : Counting boxes on pallets via 3D reconstruction from a single image Applied Intelligence, 55(10), 766.
Pham, C. H., Huynh-The, T., Sedgh-Gooya, E., El-Bouz, M., & Alfalou, A. (2024). Extension of physical activity recognition with 3D CNN using encrypted multiple sensory data to federated learning based on multi-key homomorphic encryption. Computer Methods and Programs in Biomedicine, 243, 107854.
Eddahmani, I., Pham, C. H., Napoleon, T., Badoc, I., Fouefack, J. R., & El-Bouz, M. (2023). Unsupervised learning of disentangled representation via auto-encoding : A survey. Sensors, 23(4), 2362.
Pham, C. H., Ladjal, S., & Newson, A. (2022). Pca-ae : Principal component analysis autoencoder for organising the latent space of generative networks. Journal of Mathematical Imaging and Vision, 64(5), 569-585. [[Preprint 1, Preprint 2, Paper ,Original Code, Code using DeZero ]
Delannoy, Q., Pham, C. H., Cazorla, C., Tor-Díez, C., Dollé, G., Meunier, H., ... & Rousseau, F. (2020). SegSRGAN: Super-resolution and segmentation using generative adversarial networks—Application to neonatal brain MRI. Computers in Biology and Medicine, 103755. [Paper , Python package]
Pham, C. H. Tor-Díez, C., Meunier, H., Bednarek, N., Fablet, R., Passat, N., Rousseau, F. (2019). Multiscale brain MRI super-resolution using deep 3D convolutional networks. Computerized Medical Imaging and Graphics, 77, 101647. [Paper, Code]
Conferences:
Harb, H., Benoit, D., Pham, C. H., Nasr, B., & Bert, J. (2026, September). Near Real-Time Physician Dose Prediction in Interventional Radiology Using Artificial Intelligence. In European Congress of Medical Physics (ECMP 2026).
Bert, J., Benoit, D., Pham, C. H., & Visvikis, D. (2025, November). Scout Monte Carlo : Preliminary Results of a Variance Reduction Technique for Photon Scattering Dose Calculation. In 2025 IEEE Nuclear Science Symposium (NSS), Medical Imaging Conference (MIC) and Room Temperature Semiconductor Detector Conference (RTSD) (pp. 1-1).
Harb, H., Taguelmimt, K., Abdallah, N., Pham, C. H., Nasr, B., & Bert, J. (2025, October). Machine Learning-Based Rapid Dose Estimation of Upper Extremities in Interventional Radiology. In ICRP 2025, 8th International Symposium on the System of Radiological Protection.
Pham, C. H., Díez, C. T., Meunier, H., Bednarek, N., Fablet, R., Passat, N., Rousseau, F. (2019). Simultaneous super-resolution and segmentation using a generative adversarial network: Application to neonatal brain MRI. In 2019 IEEE 16th International Symposium on Biomedical Imaging. [Paper, Code]
Díez, C. T., Pham, C. H., Meunier, H., Faisan, S., Bloch, I., Bednarek, N., R., Passat, N., Rousseau, F. (2019). Evaluation of cortical segmentation pipelines on clinical neonatal MRI data. In 41st International Engineering in Medicine and Biology Conference.
Pham, C. H., Ducournau, A., Fablet, R., & Rousseau, F. (2017, April). Brain MRI super-resolution using deep 3D convolutional networks. In Biomedical Imaging (ISBI 2017), 2017 IEEE 14th International Symposium on (pp. 197-200). IEEE. [Paper, Code]
Le-Tien, T., & Pham-Chi, H. (2014). An Approach for Efficient Detection of Cephalometric Landmarks. Procedia Computer Science, 37, 293-300.
Thesis: