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Bild Dr. Daniel Otero Baguer

Dr. Daniel Otero Baguer

Research Assistant WG Industrial Mathematics

Room: MZH 2060
Email: otero@math.uni-bremen.de
Phone: (0421) 218-63816

Projects

  1. DIAMANT - Digital Image Analysis and Imaging Mass Spectrometry to Differentiate Non-small Cell Lung Cancer (01.01.2020 - 31.12.2022)
  2. SFB 1232: Farbige Zustände - TP P02: Heuristische, statistische und analytische Versuchsplanung (01.07.2016 - 30.06.2020)

Theses (Selection)complete list

  1. Invertible U-Nets for Memory-Efficient Backpropagation (Nick Heilenkötter)

Publications (Selection)complete list

  1. D. Otero Baguer, J. Leuschner, M. Schmidt.
    Computed Tomography Reconstruction Using Deep Image Prior and Learned Reconstruction Methods.
    Inverse Problems, 36(9), IOPscience, 2020.

    DOI: https://doi.org/10.1088/1361-6420/aba415

  2. D. Otero Baguer.
    Neural Networks for solving Inverse Problems. Applications in Materials Science and Medical Imaging. (submitted).
    Dissertationsschrift, Universität Bremen, 2020.
  3. S. Dittmer, T. Kluth, D. Otero Baguer, B. Maass.
    A Deep Prior Approach to Magnetic Particle Imaging.
    Machine Learning for Medical Image Reconstruction 2020.
    Springer International Publishing, F. Deeba, P. Johnson, T. Würfl, J. C. Ye (Eds.), pp. 113-122, 2020.
  4. S. Dittmer, T. Kluth, P. Maaß, D. Otero Baguer.
    Regularization by architecture: A deep prior approach for inverse problems.
    Journal of Mathematical Imaging and Vision, :456-470, Springer Verlag, 2020.

    DOI: 10.1007/s10851-019-00923-x
    online at: http://link.springer.com/article/10.1007/s10851-019-00923-x

  5. J. Leuschner, M. Schmidt, D. Otero Baguer, P. Maaß.
    The LoDoPaB-CT Dataset: A Benchmark Dataset for Low-Dose CT Reconstruction Methods.
    Zur Veröffentlichung eingereicht.

    online at: arXiv:1910.01113