Dr. Gael Rigaud

Courses (Selection)complete list

1. Moderne Verfahren der Bildgebung und Bildverarbeitung (Sommersemester 2021)
2. Mathematische Grundlagen der Datenanalyse und Bildverarbeitung (Wintersemester 2020/2021)
3. Deep Learning Methods for Inverse Problems (Sommersemester 2020)

Publications (Selection)complete list

1. J. Gödeke, G. Rigaud.
   Imaging based on Compton scattering: model uncertainty and data-driven reconstruction methods.
   Inverse Problems, 39(3), 2023.

   DOI: 10.1088/1361-6420/acb2ed

2. C. Arndt, A. Denker, J. Nickel, J. Leuschner, M. Schmidt, G. Rigaud.
   In Focus - hybrid deep learning approaches to the HDC2021 challenge.
   Inverse Problems and Imaging, , 2022.

   DOI: 10.3934/ipi.2022061

3. G. Rigaud.
   3D Compton scattering imaging with multiple scattering: analysis by FIO and contour reconstruction.
   Inverse Problems, 37(6), 2021.

   online at: https://iopscience.iop.org/article/10.1088/1361-6420/abf22b

4. L. Kuger, G. Rigaud.
   Modeling and Reconstruction Strategy for Compton Scattering Tomography with Scintillation Crystals.
   Crystals, 11(6), 2021.

   DOI: https://doi.org/10.3390/cryst11060641

5. L. Kuger, G. Rigaud.
   Joint fan-beam CT and Compton scattering tomography: analysis and image reconstruction.
   Zur Veröffentlichung eingereicht.

   online at: https://arxiv.org/abs/2008.06699