Offre en lien avec l’Action/le Réseau : – — –/Doctorants
Laboratoire/Entreprise : IMT Toulouse et IPAL/ASTAR SIngapour
Durée : 3 ans
Contact : caroline.chaux@cnrs.fr
Date limite de publication : 2024-05-15
Contexte :
Nous proposons un sujet de thèse France – Singapour pour lequel la moitié de la thèse aura lieu en France (ITM Toulouse) et l’autre moitié à SIngapour (IPAL IRL CNRS 2955).
Sujet :
The goal of this PhD thesis is to deploy the 3D PAT scanner designed by
Jérôme Gateau at the Laboratoire d’Imagerie Biomédicale (LIB) for a routine use in biomedical studies.
This will be achieved by designing fast reconstruction methods that provide high-quality results. Depending on the candidate interests, the following axes would be considered:
• Designing implementations of the forward and adjoint models (modeled by matrix-vector products) that are fast and that incorporate the SVIR of the detector. During their preliminary works, the
partners have identified a promising approximation method of A together with the actual reconstruction algorithms. The method based on the Fourier Integral Operator form of the wave propagation equation, should be able to scale high-quality reconstructions to real data. Other types of approximation
could also be considered such as Hierarchical matrices or tensor-train decomposition.
• Designing reconstruction algorithms based on deep neural networks: such as Plug-and-Play methods or algorithm unrolling.
• Implementing an optimized high-parallel (GPU) version of the algorithms to meet with the time requirements of routine use.
• Designing automatic fine-tuning methods of the hyper-parameters involved in these reconstruction algorithms and the calibration of the parameters of A.
One outcome of this PhD project is a photoacoustic scanner that simultaneously combine, compared to standard reconstruction methods, (i) shorter acquisition times, (ii) a reconstructed image of higher resolution and contrast, and (iii) shorter computation times. This could have a great impact on the PAT community which in turn will benefit the clinical and biological communities. The candidate will be trained and could develop skills in optimization, image processing, machine learning, high performance computing and approximation theory. These competences are actively being in demand in the industry and the academic research.
Profil du candidat :
Master of computer science or applied mathematics with strong skills in signal/image processing, optimization, machine learning and numerical computations. Languages: Python/Matlab, C++/ CUDA.
Formation et compétences requises :
Master of computer science or applied mathematics with strong skills in signal/image processing, optimization, machine learning and numerical computations. Languages: Python/Matlab, C++/ CUDA.
Adresse d’emploi :
IMT Toulouse
IPAL Singapour
Document attaché : 202404260923_2024_PhD_offer_IPAL.pdf