Postdoctoral Fellow
Research group | Digital Signal Processing and Image Analysis (DSB)
Main supervisor | Sven Peter N?sholm
Co-supervisor | -
Affiliation | Department of Informatics, UiO
Contact | mohambo@ifi.uio.no
Short bio
I completed my PhD in 2021, in applied mathematics at the University of Caen Normandy in France, with a thesis titled “Fading regularization inverse methods for the identification of boundary conditions in thin plate theory”. Following that, I worked as a postdoctoral fellow on a collaborative project between the French National Institute for Research in Digital Science and Technology (INRIA) in Paris and the French energy company EDF. Currently, I am a postdoctoral research fellow at UiO under the DSTrain MSCA fellowship, working with the DSB group in the Department of Informatics on medical ultrasound elastography.
Research interests and hobbies
Broadly speaking, I am interested in applied mathematics, particularly in inverse problems and imaging. My research primarily focuses on developing non-invasive methods to recover incomplete or inaccessible information from limited measurements. This often involves using non-destructive waves and applying regularization techniques to address the inherent ill-posedness of these problems.
In my previous position, I worked on seismic data processing to image the interface separating the concrete of a hydroelectric dam and the rock on which it was built. To do this, I developed an inversion method based on the full-waveform inversion (FWI).
In my DSTrain project, I am shifting to a smaller-scale context, focusing on medical ultrasound elastography. The aim is to adapt the full waveform inversion (FWI), commonly used in seismic imaging, to estimate the physical properties of tissues—critical for tumor detection—while incorporating neural networks to accelerate simulations and enhance data analysis.
Outside of research, I enjoy playing football, hiking, cooking, as well as traveling to discover new cultures.
DSTrain project
Full Waveform Inversion for Time-Harmonic Elastography using ultrasound shear waves
Ultrasound elastography is a non-invasive and cost-effective technique for diagnosing diseases by measuring tissue stiffness. Safer and more portable than magnetic resonance elastography (MRE), it is well-suited for clinics and resource-limited settings. This study focuses specifically on time-harmonic shear waves generated by an external actuator, which offer enhanced tissue illumination and are particularly effective for imaging deeper organs.
In this work, we propose the development of an innovative processing approach based on Full Waveform Inversion (FWI). Known as a powerful tool for seismic imaging and subsurface exploration, FWI has also shown potential in medical imaging, as both fields share similar principles and techniques in signal processing. However, while historically constrained by computational burdens, advancements in technology and data science now enable its broader application.
This project aims to integrate FWI into time-harmonic shear wave elastography while also leveraging machine learning approaches, such as neural operator methods, to accelerate the computationally intensive simulations of nonlinear wavefield propagation and mode conversion. This will contribute to a significant advancement, enhancing both the efficiency and accuracy of the FWI imaging technique. An illustrative application could involve assessing cardiac health and diagnosing conditions by estimating myocardial stiffness. Validation against state-of-the-art techniques will be achieved through simulation studies, channel data recorded from elasticity phantoms, as well as in vivo data recorded using the research ultrasound scanners available in the University of Oslo laboratory.
Publications
DSTrain publications
Previous publications
Boukraa, M. A., Caillé, L., & Delvare, F. (2025). Fading regularization method for an inverse boundary value problem associated with the biharmonic equation. Journal of Computational and Applied Mathematics, 457, 116285. (https://doi.org/10.1016/j.cam.2024.116285.)
Boukraa, M. A., Audibert, L., Bonazzoli, M., Haddar, H., & Vautrin, D. (2024, June). High-Resolution Seismic Imaging for Dam-Rock Interface using Full-Waveform Inversion. In 16th International Conference on Mathematical and Numerical Aspects of Wave Propagation.
Boukraa, M. A., Bonazzoli, M., Haddar, H., Audibert, L., & Vautrin, D. (2024, June). Imaging a dam-rock interface with inversion of a full elastic-acoustic model. In ICIPE 2024-11th International Conference on Inverse Problems in Engineering: Theory and Practice.
Boukraa, M. A., Audibert, L., Bonazzoli, M., Haddar, H., & Vautrin, D. (2024). Imagerie d’interface barrage-fondation par inversion de forme d'onde complète. In E3S Web of Conferences (Vol. 504, p. 04002). EDP Sciences. (https://doi.org/10.1051/e3sconf/202450404002).
Boukraa, M. A., Amdouni, S., & Delvare, F. (2023). Fading regularization FEM algorithms for the Cauchy problem associated with the two‐dimensional biharmonic equation. Mathematical Methods in the Applied Sciences, 46(2), 2389-2412. (https://doi.org/10.1002/mma.8651).
Boukraa, M. A. (2021). Méthodes inverses à régularisation évanescente pour l'identification de conditions aux limites en théorie des plaques minces (Doctoral dissertation, Normandie Université).