This image shows Bernadette  Hahn-Rigaud

Bernadette Hahn-Rigaud

Prof. Dr.

Chairholder OIP
Dept. of Mathematics, IMNG
Optimization and Inverse Problems


Pfaffenwaldring 57
70569 Stuttgart
Room: 8.164

Office Hours

on appointment


in German : English to follow

Dynamical Inverse Problems

Bildgebende Verfahren

Data Analyis / Datenanalyse und Bildverarbeitung


  1. 2024

    1. M. Nitzsche and B. N. Hahn, Dynamic image reconstruction in MPI with RESESOP-Kaczmarz. 2024.
  2. 2023

    1. B. N. Hahn, G. Rigaud, and R. Schmähl, A class of regularizations based on nonlinear isotropic diffusion for inverse problems, IMA Journal of Numerical Analysis, Feb. 2023.
    2. B. Hahn and B. Wirth, Convex reconstruction of moving particles with inexact motion model, PAMM, vol. 23, no. 2, Sep. 2023.
    3. M. S. Feinler and B. N. Hahn, Retrospective Motion Correction in Gradient Echo MRI by Explicit Motion Estimation Using Deep CNNs. 2023.
  3. 2022

    1. M. Nitzsche, H. Albers, T. Kluth, and B. Hahn, Compensating model imperfections during image reconstruction via Resesop, International Journal on Magnetic Particle Imaging, p. Vol 8 No 1 Suppl 1 (2022), 2022.
    2. B. N. Hahn, M.-L. K. Garrido, C. Klingenberg, and S. Warnecke, Using the Navier-Cauchy equation for motion estimation in dynamic imaging, Inverse Problems and Imaging, vol. 0, no. 0, p. 0, 2022.
  4. 2021

    1. B. N. Hahn, M. L. Kienle-Garrido, and E. T. Quinto, Microlocal properties of dynamic Fourier integral operators, 2021.
    2. B. N. Hahn, Motion compensation strategies in tomography, 2021.
  5. 2020

    1. G. Rigaud and B. N. Hahn, Reconstruction algorithm for 3D Compton scattering imaging with incomplete data, Inverse Problems in Science and Engineering, vol. 29, no. 7, pp. 967--989, 2020.
    2. A. P. Polyakova, I. E. Svetov, and B. N. Hahn, The Singular Value Decomposition of the Operators of the Dynamic Ray Transforms Acting on 2D Vector Fields, in Numerical Computations: Theory and Algorithms, Cham, 2020, pp. 446--453.
    3. B. N. Hahn, M. L. Kienle-Garrido, C. Klingenberg, and S. Warnecke, Using the Navier-Cauchy equation for motion estimation in dynamic imaging. 2020.
    4. S. E. Blanke, B. N. Hahn, and A. Wald, Inverse problems with inexact forward operator: iterative regularization and application in dynamic imaging, Inverse Problems, vol. 36, no. 12, p. 124001, 2020.
  6. 2019

    1. Mathematisches Forschungsinstitut Oberwolfach, Tomographic Inverse Problems: Theory and Applications, Workshop Reports, 2019.
    2. T. Kluth, B. N. Hahn, and C. Brandt, Spatio-temporal concentration reconstruction using motion priors in magnetic particle imaging, in Proc. Int. Workshop Magnetic Particle Imaging, 2019.
    3. B. N. Hahn and M.-L. Kienle Garrido, An efficient reconstruction approach for a class of dynamic imaging operators, Inverse Problems, vol. 35, no. 9, p. 094005, 2019.
  7. 2018

    1. G. Rigaud and B. N. Hahn, 3D Compton scattering imaging and contour reconstruction for a class of Radon transforms, Inverse Problems, vol. 34, no. 7, p. 075004, 2018.
  8. 2017

    1. B. N. Hahn, Motion Estimation and Compensation Strategies in Dynamic Computerized Tomography, Sensing and Imaging, vol. 18, no. 10, pp. 1–20, 2017.
    2. B. N. Hahn, A motion artefact study and locally deforming objects in computerized tomography, Inverse Problems, vol. 33, no. 11, p. 114001, 2017.
  9. 2016

    1. B. N. Hahn and E. T. Quinto, Detectable singularities from dynamic Radon data, SIAM J. Imaging Sciences, vol. 9, no. 3, pp. 1195–1225, 2016.
    2. B. N. Hahn, Null space and resolution in dynamic computerized tomography, Inverse Problems, vol. 32, no. 2, p. 025006, 2016.
  10. 2015

    1. B. N. Hahn, Dynamic linear inverse problems with moderate movements of the object: Ill-posedness and regularization, Inverse Problems & Imaging, vol. 9, no. 2, pp. 395–413, 2015.
    2. D. Gerth, B. N. Hahn, and R. Ramlau, The method of the approximate inverse for atmospheric tomography, Inverse Problems, vol. 31, no. 6, p. 065002, 2015.
  11. 2014

    1. B. N. Hahn, Reconstruction of dynamic objects with affine deformations in computerized tomography, Journal of Inverse and Ill-posed Problems, vol. 22, no. 3, pp. 323–339, 2014.
    2. B. N. Hahn, Efficient algorithms for linear dynamic inverse problems with known motion, Inverse Problems, vol. 30, no. 3, p. 035008, 2014.
  12. 2013

    1. B. N. Hahn, A. K. Louis, M. Maisl, and C. Schorr, Combined reconstruction and edge detection in dimensioning, Meas. Sci. Technol, vol. 24, no. 12, p. 125601, 2013.
  13. 2012

    1. B. N. Hahn and A. K. Louis, Reconstruction in the three-dimensional parallel scanning geometry with application in synchrotronbased x-ray tomography, Inverse Problems, vol. 28, no. 4, p. 045013, 2012.
    2. B. N. Hahn, Reconstruction of dynamic objects in computerized tomography, Oberwolfach Reports, vol. 9, pp. 3069-3071B, 2012.

Current semester

Current courses can be found on the Teaching Page or directly in Campus.

Previous semesters

Winter term 2022/23:

  • Mathematical image processing
  • associated lecture (PD Dr. Gael Rigaud):
    Masterseminar: Machine Learning meets inverse problems

Summer term 2022:

  • Introduction to Inverse Problems

Winter term 2021/22:

  • Introduction to Optimization
  • associated lecture (PD Dr. Gael Rigaud):
    Masterseminar: Modern Challenges in Image processing and Imaging

Summer term 2021:

  • Mathematical Image Processing
  • Seminar zu Optimierung und inversen Problemen

Winter term 2020/21:

  • Introduction to Optimization
  • Seminar: Medizinische Bildgebung

Sommersemester 2020:

  • Regularization of Inverse problems
    theorie and application
  • Seminar: Sparsity und Compressed Sensing

English to follow

  • Lecture award of the student council (Fachgruppe) for digital teaching (summer term 2020)
  • EAIP Young Scientist Award for distinguished contributions to inverse problems (2018)
  • Highlights of IOP Inverse Problems (2012, 2014, 2015, 2016, 2017)
To the top of the page