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Book chapter

    Andres, M., Blum, H., Brandt, C., Carstensen, C., Maass, P., Niebsch, J., Rademacher, R., Ramlau, R., Schröder, A., Stephan, E.-P., and Wiedemann, S.: Process Machine Interactions, Adaptive finite elements and mathematical optimization methods. Lectures Notes in Production Engineering. Springer, 2013.
doi:DOI:10.1007/978-3-642-32448-2.

    Brandt, C., Krause, A., Niebsch, J., Vehmeyer, J., Brinksmeier, E., Maass, P., and Riemer, O.: Process Machine Interactions, Surface Generation Process with Consideration ot the Balancing State in Diamond Machining. Lectures Notes in Production Engineering. Springer, 2013.
doi:DOI: 10.1007/978-3-642-32448-2.

    Piotrowska-Kurczewski, I., Brandt, C., Maass, P., and Riemer, O.: Micro Metal Forming, chapter Simulation technologies - Inverse Modelling, pages 368–379. Springer, 2013.

    Brandt, C., Piotrowska, I., Karimi, H., Niebsch, J., Ramlau, R., Krause, A., Riemer, O., and Maass, P.: Process machine interaction model for turning processes. International Journal of Control Theory and Applications, 1(2):145–153, 2008.

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Conference proceedings (reviewed)

    Schmidt, C. and Brandt, C.: Dynamic concentration reconstruction for magnetic particle imaging using splines. Proceedings of the International Workshop on Magnetic Particle Imaging 2020, March 17-19. 2020, Würzburg, 2019.

    Kluth, T.; Hahn, B.N. and Brandt, C.: Spatio-temporal concentration reconstruction using motion priors in magnetic particle imaging. Proceedings of the International Workshop on Magnetic Particle Imaging 2019, March 17-19. 2016, New York, USA, 2019.

    Brandt, C. and Hauptmann, A.: Fast temporal regularized reconstructions for magnetic particle imaging. Proceedings of the International Workshop on Magnetic Particle Imaging 2019, March 17-19. 2016, New York, USA, 2019.

    Storath, M., Brandt, C., Hofmann, M., Knopp, T. , Weber, A., Weinmann, A.: Fused lasso regularization for magnetic particle imaging. Proceedings of the International Workshop on Magnetic Particle Imaging 2016, March 16-18. 2016, Lübeck, Germany, 2016.

    Brandt, C., Niebsch, J., and Vehmeyer, J.: Modelling of ultra-precision turning process in consideration of unbalances. In Outeiro, J.C., editor, Proceedings of the 13th CIRP Conference on Modeling of Machining Operations, May 12-13. 2011, Sintra, Portugal, volume 223, pages 839–848. 2011. www.scientific.net/AMR.223.839>

    Niebsch, J., Ramlau, R., and Brandt, C.: On the interaction of unbalances and surface quality in ultra-precision cutting machinery. In SIRM 2011, Darmstadt, Germany. 2011.

    Brandt, C., Niebsch, J., Maass, P., and Ramlau, R.: Simulation of process machine interaction for ultra precision turning. In Proceedings of the 2nd International Conference on Process Machine Interactions, June 10-11, 2010, Vancouver, Canada. 2010.

    Brandt, C., Krause, A., Brinksmeier, E., and Maass, P.: Force modelling in diamond machining with regard to the surface generation process. In Proceedings of the 9th International Conference and Exhibition on Laser Metrology, machine tool, CMM and robotic performance, LAMDAMAP 2009, London, 30.06.-02.07.2009, pages 377–386. 2009.

    Gossiaux, P.B., Peigné, S., Brandt, C., and Aichelin, J.: Energy loss of a heavy quark produced in a finite-size quark-gluon plasma
doi:10.1088/0954-3899/34/8/S103. QM2006 Proceedings; 19th International Conference on Ultra-Relativistic Nucleus-Nucleus Collisions (QM2006), Shanghai, China, November 14-20, 2006.

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Find my papers on researchgate

Magnetic Particle Imaging (MPI) is a novel imaging modality for biomedical diagnostics that determines the spatial distribution of magnetic nanoparticles by measuring the non-linear magnetization response of the particles to an applied magnetic field. The advantages of MPI are the high dynamic spatial and temporal resolution and that it does not employ any ionizing radiation.

Actual research projects on MPI

Flow estimation with a priori edge information for MPI/MRI data , joint work with Tobias Kluth

Joint reconstruction in multi-color MPI, joint work with Martin Hofmann and Tobias Knopp

Approximation error modelling for model-based MPI, joint work with Aku Seppänen

Time based regularization for 4D MPI, joint work Andreas Hauptmann

Reconstruction methods for dynamic inverse problems , PhD project of Christiane Schmidt

Blood flow modeling and estimation by magnetic particle imaging , PhD project of Stephanie Blanke

The main objective of this research is the development of mathematical methods for three imaging modalities in biological and medical applications: fluorescence microscopy (FM), photo-acoustic tomography (PAT) and magnetic particle imaging (MPI). All imaging applications have in common that the desired object such as in PAT and MPI the cancer cell in the human body is not directly observable but can be measured only indirectly.

In order to reconstruct the desired object, one has to solve the so-called inverse problem. In this project, mathematical methods for solving inverse problems are developed which consider modelling errors and uncertainties of the underlying models in the inversion. It is expected that the image reconstruction quality will be increased significantly in all three applications. In particular, the improvements are assumed to contribute to the development of PAT and MPI as medical imaging techniques in clinical practice.

This project is founded by the Academy of Finland.

Related Publications:

    Brandt, C.; Seppänen, A. : Recovery from errors due to domain truncation in magnetic particle imaging -- approximation error modeling approach. Journal of Mathematical Imaging and Vision, 2018.
10.1007/s10851-018-0807-z

Novel X-ray sources (in particular FELs) allow for the first time to study complex chemical reactions and catalysis in time-dependent manner. While x-ray diffraction gives access to the structure of the underlying system (atomic position), x-ray emission spectroscopy is a complementary technique, to gain chemical knowledge (such as, for example the spin and oxidation state of a particular reaction center). The time-dependent observation of the breaking and formation of electronic bonds is, however, still a delicate task and relies on the interpretation of experimental data based on models.

At the current stage, a few pioneering groups perform x-ray scattering and x-ray emission spectroscopy within one experimental set up and build models to interpret these data. The data analysis and the reconstruction of the underlying physical quantities (determination of the electron density by solving the phase problem of crystallography) are, however, performed independently and separately for each method. In this project, we aim for the next rigorous step, by developing a common data analysis, reconstruction and model building approach combining x-ray diffraction and emission spectroscopy. This novel holistic approach has the potential to strongly improve on the resolution of the chemically-relevant valence electronic density and their current densities.

This project is founded by the DESY Strategy Fund. It is a joint project with Prof. N. Rohringer and Prof. S. Techert from DESY.

The proposed interdisciplinary project between the natural and mathematical/information sciences is understood as a kick-of project to develop novel x-ray data analysis methods for combined x-ray diraction and x-ray emission spectroscopy measurements at high-brilliance x-ray sources. While coherent x-ray diraction gives access to the structure (position of atoms) of a chemical compound or reaction unit, x-ray emission spectroscopy is a complementary and sensitive probe to the changes of the chemical bonds. The interpretation of the latter strongly relies on comparison with theoretically calculated spectra. Pioneering experiments at storage-ring based x-ray sources and x-ray free electron lasers (XFELs) have shown the possibility for combining x-ray diraction, x-ray scattering and x-ray emission spectroscopy in one high-quality experiment. Currently, the data analysis and reconstruction of the underlying physical quantities of interest (electron density, oxidation state, electron density, etc.) are undertaken independently from the two techniques. Here, we aim for a common data analysis and density reconstruction method, based on an underlying common electronic structre (quantum chemistry) model. Experimental x-ray diffraction and x-ray emission data will be directly implemented as constraints in the minimization approaches of ab-initio quantum chemistry methods, in the spirit of quantum crystallography. In this way chemical and structural information can be reconstructed in a coherent way.

This project is founded by the BMBF. It is a joint project with Prof. N. Rohringer from DESY/Department of physics(UHH).

    Nawwas, L., Brandt, C., Szwargulski, P., Knopp, T., and Möddel, M.: Reduction of Bias for Sparsity Promoting Regularization in MPI , submitted to Interational Journal of Magnetic particle imaging.


    Brandt, C. and Hauptmann, A.: Real time reconstruction for 4D Magnetic Particle Imaging.

    Brandt, C. and Schmidt, C.: Modeling magnetic particle imaging for dynamic tracer concentrations , submitted to Journal of Sensing and Imaging

I am currently working on inversion methods for magnetic particle imaging and as well as for inverse problems in X-ray science. Moreover, I am interested in dynamic inverse problems and regularization methods for these problems.

More generally my research interests are :

• Medical and biological imaging
• Modelling and simulation
• Regularization with sparsity constraints
• Dynamic inverse problems
• Bayesian inversion and approximation error modelling
• Coupled inverse problems in X-ray laser physics
• Phase retrival

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