Leonhard Rist

Leonhard Rist, M. Sc.

Researcher

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

Room: Room 09.132
Martensstr. 3
91058 Erlangen

  • Since 02/2021:
    PhD Student at the Pattern Recognition Lab, FAU Erlangen-Nürnberg in cooperation with Siemens Healthineers AG, Forchheim
    Research Topic: Cerebral vasculature analysis for Computed Tomography
  • 04/2018 – 01/2021:
    Master’s Degree in Medical Engineering with focus on Medical Imaging and Data Processing, FAU Erlangen-Nürnberg
    Master’s Thesis: “Geometric Deep Learning for Multifocal Diseases”
  • 10/2014 – 03/2018:
    Bachelor’s Degree in Medical Engineering with focus on Imaging Systems, FAU Erlangen-Nürnberg
    Bachelor’s Thesis: “A Flexible Calibration Phantom for FD-CT using Cross-Ratios”

No projects found.

Collaboration with Siemens Healthineers for the analysis and visualization of brain vasculature in CTA scans

2022

Journal Articles

Conference Contributions

2021

Miscellaneous

2018

Conference Contributions

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

    • 2 SWS; Expected participants: 450; ECTS-Studium (ECTS-Credits: 2,5), Unterrichtssprache Englisch
    • Termin:
      • Fr 8:00-10:00, Room 0.01-142 CIP (exclude vac) ICS
      • Mo 12:00-14:00, Room 0.01-142 CIP (exclude vac) ICS
      • Mi 16:00-18:00, Room 0.01-142 CIP (exclude vac) ICS
      • Do 14:00-16:00, Room 0.01-142 CIP (exclude vac) ICS
      • Di 18:00-20:00, Room 0.01-142 CIP (exclude vac) ICS

Vorlesung (VORL)

  • Deep Learning

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

    The following lectures are recommended:

    • Introduction to Pattern Recognition (IntroPR)
    • Pattern Recognition (PR)

    Application via https://www.studon.fau.de/crs3888652.html

    • 2 SWS; Expected participants: 400; ECTS-Studium (ECTS-Credits: 2,5), Unterrichtssprache Englisch
    • Termin:
      • Mi 14:15-15:45, Room H7 (exclude vac) ICS

Student Title Type Status
Unfolding of Pancreas and Surrounding Vessel Structures MA thesis open
Main Cerebral Vessel Labeling using Graph Neural Networks MA thesis open
Stefan Ringer Extraction of Treatment Margins from CT Scans for Evaluation of Lung Tumor Cryoablation MA thesis running
Ibrahim Maniaa Fully Automated Segmentation of Subcutaneous Fat in CT Images MA thesis running
Eduard Reger Modeling of Randomized Cerebrovascular Trees for Artifical Data Generation using Blender MA thesis running
Antonia Popp Thrombus detection using nnDetection Project finished
Tasnim Nova Post-Processing of DTF-Skeletonizations Project running
Jad Kassam Detection of Large Vessel Occlusions using Graph Deep Learning MA thesis finished