Publikationen der AG Technomathematik

Zeitschriftenartikel (11)

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

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

2. S. Schulze, J. Leuschner, E. King.
   Blind Source Separation in Polyphonic Music Recordings Using Deep Neural Networks Trained via Policy Gradients.
   MDPI Open Access Journals Signals, 2(4):637-661, 2021.

   DOI: 10.3390/signals2040039
   online unter: https://www.mdpi.com/2624-6120/2/4/39

3. A. Denker, M. Schmidt, J. Leuschner, P. Maaß.
   Conditional Invertible Neural Networks for Medical Imaging .
   MDPI Journal of Imaging, Inverse Problems and Imaging 7(11), 243 S., 2021.

   DOI: 10.3390/jimaging7110243

4. T. Boskamp, R. Casadonte, L. Hauberg-Lotte, S. Deininger, J. Kriegsmann, B. Maass.
   Cross-Normalization of MALDI Mass Spectrometry Imaging Data Improves Site-to-Site Reproducibility.
   Analytical Chemistry, 93(30):10584-10592, 2021.

   online unter: https://doi.org/10.1021/acs.analchem.1c01792

5. S. Dittmer, T. Kluth, M. Henriksen, P. Maaß.
   Deep image prior for 3D magnetic particle imaging: A quantitative comparison of regularization techniques on Open MPI dataset.
   International Journal on Magnetic Particle Imaging, 7(1), 2021.

   online unter: https://journal.iwmpi.org/index.php/iwmpi/article/view/148

6. J. Le Clerc Arrastia, N. Heilenkötter, D. Otero Baguer, L. Hauberg-Lotte, T. Boskamp, S. Hetzer, N. Duschner , J. Schaller , P. Maaß.
   Deeply Supervised UNet for Semantic Segmentation to Assist Dermatopathological Assessment of Basal Cell Carcinoma.
   MDPI Journal of Imaging, 71 7(4), Meisenbach Verlag, Bamberg, 2021.

   DOI: 10.3390/jimaging7040071

7. M. Möddel, F. Griese, T. Kluth, T. Knopp.
   Estimating the Spatial Orientation of Immobilized Magnetic Nanoparticles with Parallel-Aligned Easy Axes.
   Physical Review Applied, 16(4), L041003 S., 2021.
8. J. Leuschner, M. Schmidt, D. Otero Baguer, P. Maaß.
   LoDoPaB-CT, a benchmark dataset for low-dose computed tomography reconstruction.
   Scientific Data, 8(109), 2021.

   DOI: 10.1038/s41597-021-00893-z

9. 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

10. J. Leuschner, M. Schmidt, P. Ganguly, V. Andriiashen, S. Coban, A. Denker, D. Bauer, A. Hadjifaradji, K. Batenburg, B. Maass, M. von Eijnatten.
    Quantitative Comparison of Deep Learning-Based Image Reconstruction Methods for Low-Dose and Sparse-Angle CT Applications.
    MDPI Journal of Imaging, 7(3), 44 S., 2021.

    DOI: 10.3390/jimaging7030044
    online unter: https://www.mdpi.com/2313-433X/7/3/44

11. P. Fernsel.
    Spatially Coherent Clustering Based on Orthogonal Nonnegative Matrix Factorization.
    MDPI Journal of Imaging, 7(10), 2021.

    DOI: 10.3390/jimaging7100194
    online unter: https://www.mdpi.com/2313-433X/7/10/194

Tagungsbeiträge (2)

1. M. Schmidt.
   Around the clock - capsule networks and image transformations.
   PAMM.
   Proceedings in Applied Mathematics and Mechanics, 20(1):e202000179, 2021.

   DOI: 10.1002/pamm.202000179
   online unter: https://onlinelibrary.wiley.com/doi/abs/10.1002/pamm.202000179

2. M. Schmidt, A. Denker, J. Leuschner.
   The Deep Capsule Prior - advantages through complexity.
   GAMM 91st Annual Meeting of the international Association of Applied Mathematics and Mechanics, online, 15.03.2021 - 19.03.2021.
   Proceedings in Applied Mathematics & Mechanics, 21(1), WILEY-VCH, 2021.

   DOI: 10.1002/pamm.202100166

Qualifikationsarbeiten (1)

1. G. Sfakianaki.
   Regularization of ill-posed inverse problems with tolerances and sparsity in parameter space.
   Dissertationsschrift, Universität Bremen, 2021.

   DOI: 10.26092/elib/1065
   online unter: https://media.suub.uni-bremen.de/bitstream/elib/5269/1/Georgia_Sfakianaki_PhD_Dissertation_2021_final_pdfA.pdf

Preprints (1)

1. P. Fernsel, P. Maaß.
   Regularized Orthogonal Nonnegative Matrix Factorization and K-means Clustering.
   Zur Veröffentlichung eingereicht.

   online unter: https://arxiv.org/abs/2112.07641