Context CREATIS opens a Master internship of 5-6 months to address new questions in the emerging field of X-ray spectral imaging. CREATIS is a research unit of CNRS/INSERM/INSA Lyon/University of Lyon devoted to medical imaging. Its different teams target various modalities (X-rays, Ultrasounds, MRI, PET and optics) and carry research from signal processing to medical applications. The candidate will join the “Tomographic Imaging and Radiotherapy” team, which has internationally recognized expertise in X-ray tomography and inverse problems.
Project X-ray “color” or “spectral” computed tomography (CT) is a new imaging modality that is raising increasing interest in radiology. Thanks to a new detector technology that can discriminate X-ray photons depending on their energy [1], it is possible to reconstruct the constituents of the human body such as bone, water, fat or concentration in contrast agents [2]. Although recent works have shown the feasibility of spectral CT systems, many questions are still open such as the best way to decompose sinograms before object reconstruction.
This internship may lead to a PhD position in the same field.
Keywords X-Ray Imaging, material decomposition, inverse problem.
Work Plan The goal of the internship is to provide a new decomposition method able to include appropriate a priori information in the sinogram domain. The decomposition problem can be written as a non-linear inverse problem. First, appropriate priors will be determined. Second, the non-linear inverse problem will be solved using an approach compatible with the retained priors. The student will implement and test his approach on synthetic data.
Salary 436€ net monthly
Skills The student must have a strong background in medical imaging, image processing, and inverse problem. Knowledge in radiation physics would be appreciated but is not required. Programming skills: Matlab, C, C++.
How to apply?
Send your CV and academic records to
Nicolas Ducros | nicolas.ducros@creatis.insa-lyon.fr |
Simon Rit | simon.rit@creatis.insa-lyon.fr |
Françoise Peyrin | francoise.peyrin@creatis.insa-lyon.fr |
References
[1] K. Taguchi et al, “Vision 20/20: Single photon counting x-ray detectors in medical imaging,” Medical Physics, 40, 100901, 2013.
[2] H. Gao et al, “Multi-energy CT based on a prior rank, intensity and sparsity model (PRISM)”, Inverse Problems, 27, 115012, 2011.