Maximilian Rohleder

Maximilian Rohleder, M. Sc.

Researcher

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

Room: Room 09.153
Martensstr. 3
91058 Erlangen

Academic CV

  • Visiting Researcher at West China Hospital and Sichuan University, Sichuan Province, China (06/2024 – 08/2024)
    • Observed imaging workflow in the operating room for spinal surgeries
    • Led efforts to improve image quality to improve clinical value of imaging modality
  • Visiting Researcher at I-Star Laboratories, Johns Hopkins University, Baltimore, USA (03/2022 – 09/2022)
    • Collaborative project between Johns Hopkins, FAU and Siemens Healthineers
    • Supervised by Prof. Jeffrey Siewerdsen, head of I-Star Labs (https://istar.jhu.edu)
    • Investigated the subject of Parametric Metal Artifact Avoidance resulting in publication and oral presentation at SPIE 2023 in San Diego.
  • PhD Researcher, Siemens Healthineers & FAU, Erlangen (10/2021 – now)
    • Focus: Improving image quality of intraoperative Cone-Beam CT imaging
    • Metal Artifact Avoidance through trajectory optimization
    • Leading internal pre-development project at C-Arms R&D department from concept to validated prototype
  • Master of Science, Medical Engineering, FAU, Erlangen (10/2019 – 10/2021)
    • Track: Health- and Medical Data Analytics and Entrepreneurship
    • 01/2020 – 10/2021: Working Student @ Siemens Healthineers, Forchheim
    • Winter ’20: Erasmus Exchange to Instituto Superior Técnico, Lisbon, Portugal [Link]
    • Thesis: Segmentation of Metal Volumes from Cone-Beam CT Projection Data for Metal Artefact Reduction
      • Cooperation with Siemens Healthineers, Mobile C-Arms Division, Forchheim
  • Undergraduate Visiting Researcher, Radiological Sciences Laboratory, Stanford University, California, USA (06/2019 – 09/2019)
    • Bachelor level research on material decomposition for dual energy CT imaging
    • Investigated Deep Learning approach to material decomposition
    • Supervised by Prof. Adam Wang, head of Wang Group (https://wanggroup.stanford.edu/)
  • Bachelor of Science, Medical Engineering, FAU, Erlangen (10/2016 – 10/2019)
    • Track: Medical Image Processing
    • 01/2018 – 01/2019: Working Student @ Methodpark Engineering, Erlangen Tennenlohe
    • Summer ’19: Research Visit to Stanford University, Stanford, California
    • Thesis: A Deep Learning Approach to Material Decomposition on Dual Energy Computed Tomography Data
      • Cooperation with Stanford University, Radiological Sciences Department, Wang Group, California [Link]

Supervised student projects

Type Title Status
Project Oriented Bounding Box Detection of Metallic Objects in X-Ray Images finished
Project Screw Detection in X-Ray Images using Detection Transformer Networks finished
MA thesis Generalizable X-Ray View Synthesis finished
MA thesis End-to-end detection and 3D localization of implants from multi-view images for surgical CBCT metal artifact avoidance running
MA thesis Development of an Oriented Bone Detection Algorithm on X-Ray Images finished
Project Geometric Domain Adaptation for CBCT Segmentation finished
Project Realistic Simulation of Collimated X-Ray images for Collimator Edge Segmentation using Deep Learning finished
BA thesis Projection Domain Metal Segmentation with Epipolar Consistency using Known Operator Learning finished
MA thesis Automatic Rotation of Spinal X-Ray Images finished
BA thesis Cone-Beam CT X-Ray Image Simulation for the Generation of Training Data finished