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Magnetic Resonance Imaging (MRI)

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  • An AI-based framework for visualizing and analyzing massive amounts of 4D tomography data for beamline end users
  • An AI-based framework for visualizing and analyzing massive amounts of 4D tomography data for beamline end users
  • An AI-based framework for visualizing and analyzing massive amounts of 4D tomography data for beamline end users

Magnetic Resonance Imaging (MRI)

Julian Hoßbach

Julian Hoßbach, M. Sc.

Department of Computer Science
Chair of Computer Science 5 (Pattern Recognition)

Room: Room 09.153
Martensstr. 3
91058 Erlangen
  • Phone number: +49 9131 85-25246
  • Email: julian.hossbach@fau.de
  • Website: https://lme.tf.fau.de/person/hossbach/
Profile picture of the MRI group at the PRS 2022
Group picture of the MRI group
MRI, or Magnetic Resonance Imaging, is a non-invasive medical imaging technique that provides detailed pictures of the body's internal structures using magnetic fields and radio waves.At our research group, we are committed to advancing MRI technology and its applications. Our research covers a wide range of aspects within MRI, including but not limited to reconstruction, segmentation, and artifact reduction. Through cutting-edge algorithms and methodologies, we aim to improve image quality, enhance anatomical delineation, and reduce unwanted artifacts.

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Projects

3-D Multi-Contrast CINE Cardiac Magnetic Resonance Imaging

Magnetic resonance imaging (MRI) is a non-invasive imaging technique which is well suited for the diagnosis and monitoring of cardiovascular diseases because of its ability of visualizing the anatomy and the functional information of the heart. Additionally, with this technique a diversity of image contrasts is provided. However, cardiovascular MRI is challenging due to e.g. myocardial contraction and respiratory motion and thus not well-established for the clinical practice yet.

With iterative reconstruction methods, the acquisition time can be clearly reduced and the artifacts minimized at the same time. With the help of these methods a representation of the heart with a well spatial and temporal resolution (4-D representation) can be created.

Additionally, quantitative representation of physical relaxation times can be generated with so-called mapping techniques based on these different image contrasts. The aim of this PhD project is the extension of the temporal 3-D representation imaging technique for the heart with such a multi-contrast dimension. This extra dimension can lead to an enhanced separation between pathological and healthy myocardial tissues.

→ More information

Publications

  • Hoppe E., Körzdorfer G., Nitka M., Würfl T., Wetzl J., Lugauer F., Schneider M., Pfeuffer J., Maier A.:
    Deep Learning for Magnetic Resonance Fingerprinting: Accelerating the Reconstruction of Quantitative Relaxation Maps
    Proceedings of the Joint Annual Meeting ISMRM-ESMRMB (26th Annual Meeting & Exhibition) (Paris, France)
    In: Proceedings of the Joint Annual Meeting ISMRM-ESMRMB (26th Annual Meeting & Exhibition) 2018
    URL: https://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2018/Hoppe18-DLF.pdf
    BibTeX: Download
  • Pfaff L., Wagner F., Hoßbach J., Preuhs E., Maul N., Thies M., Denzinger F., Nickel MD., Wuerfl T., Maier A.:
    Robust multi-contrast MRI denoising using trainable bilateral filters without noise-free targets
    International Symposium on Biomedical Imaging (ISBI)
    BibTeX: Download
  • Pfaff L., Wagner F., Hoßbach J., Preuhs E., Gadjimuradov F., Benkert T., Nickel MD., Wuerfl T., Maier A.:
    Unsupervised denoising of prostate DWI
    ISMRM
    BibTeX: Download

Persons

Badhan Das

Badhan Das, M. Sc.

  • Email: badhan.das@fau.de
  • LinkedIn: Page of Badhan Das
More › Details for Badhan Das
Dr.-Ing. Paula Andrea Pérez-Toro

Dr.-Ing. Paula Andrea Pérez-Toro

  • Phone number: +49 9131 85-27137
  • Email: paula.andrea.perez@fau.de
  • Website: https://lme.tf.fau.de/person/perez
  • Twitter: Page of Paula Andrea Pérez-Toro
  • GitHub: Page of Paula Andrea Pérez-Toro
  • Google Scholar: Page of Paula Andrea Pérez-Toro
More › Details for Paula Andrea Pérez-Toro
Laura Pfaff

Laura Pfaff, M. Sc.

  • Phone number: +49 9131 85-25246
  • Email: laura.pfaff@fau.de
  • Website: https://lme.tf.fau.de/person/pfaff/
More › Details for Laura Pfaff
Zijin Yang

Zijin Yang, M. Sc.

  • Phone number: +49 9131 85-28982
  • Email: michael.yang@fau.de
  • Website: https://lme.tf.fau.de/person/myang/
More › Details for Zijin Yang
Friedrich-Alexander-Universität Erlangen-Nürnberg
Lehrstuhl für Mustererkennung (Informatik 5)

Martensstr. 3
91058 Erlangen
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