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Zijin Yang, M. Sc.

Researcher

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

Room: Room 09.130
Martensstr. 3
91058 Erlangen

  • Since 08/2020:
    Ph.D. Student at Pattern Recognition Lab, FAU Erlangen-Nürnberg in Cooperation with University of Würzburg
  • 10/2017 – 06/2020:
    M. Sc. Medical Engineering (Medical Image and Data Processing), FAU Erlangen-Nürnberg

2020

  • Intelligent MR Diagnosis of the Liver by Linking Model and Data-driven Processes (iDELIVER)

    (Third Party Funds Single)

    Term: August 3, 2020 - March 31, 2023
    Funding source: Bundesministerium für Bildung und Forschung (BMBF)

    The project examines the use and further development of machine learning methods for MR image reconstruction and for the classification of liver lesions. Based on a comparison model and data-driven image reconstruction methods, these are to be systematically linked in order to enable high acceleration without sacrificing diagnostic value. In addition to the design of suitable networks, research should also be carried out to determine whether metadata (e.g. age of the patient) can be incorporated into the reconstruction. Furthermore, suitable classification algorithms on an image basis are to be developed and the potential of direct classification on the raw data is to be explored. In the long term, intelligent MR diagnostics can significantly increase the efficiency of use of MR hardware, guarantee better patient care and set new impulses in medical technology.

No publications found.

Übung (UE)

  • Deep Learning Exercises

    This course will be held online until the coronavirus pandemic is contained to such an extent that the Bavarian state government can allow face-to-face teaching again. Information regarding the online teaching will be added to the studon course

    • Wed 16:00-18:00, Room 0.01-142 CIP
    • Fri 8:00-10:00, Room 0.01-142 CIP
    • Thu 14:00-16:00, Room 0.01-142 CIP
    • Mon 12:00-14:00, Room 0.01-142 CIP
    • Tue 18:00-20:00, Room 0.01-142 CIP
  • Deep Learning Exercises

    This course will be held online until the coronavirus pandemic is contained to such an extent that the Bavarian state government can allow face-to-face teaching again. Information regarding the online teaching will be added to the studon course

    • Mon 12:00-14:00, Room 0.01-142 CIP
    • Tue 18:00-20:00, Room 0.01-142 CIP
    • Thu 14:00-16:00, Room 0.01-142 CIP
    • Fri 8:00-10:00, Room 0.01-142 CIP
    • Wed 16:00-18:00, Room 0.01-142 CIP

Vorlesung (VORL)

  • Deep Learning

    Information regarding the online teaching will be added to the studon course

    • Fri 8:15-9:45, Room H7
  • Deep Learning

    Information regarding the online teaching will be added to the studon course

    • Fri 8:15-9:45, Room H7