Marc Vornehm

Marc Vornehm, M. Sc.

Department Artificial Intelligence in Biomedical Engineering (AIBE)
W3-Professur für Computational Imaging

Room: Room 2.02
Werner-von-Siemens Str. 61
91052 Erlangen

Office hours

by appointment

My research focuses on Deep Learning-based reconstruction of accelerated dynamic MRI acquisitions in the cardiac domain, for instance time-resolved cine imaging of the heart. Other research interests include segmentation and registration tasks in cardiac MRI. Previously, I have worked on 4D-CT for radiation therapy planning.

If you are interested in a student project/thesis, feel free to contact me via e-mail.

Academic CV

  • Since 10/2021
    Ph.D. Candidate at Computational Imaging Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg
    in collaboration with Siemens Healthineers (Magnetic Resonance), Erlangen
  • 10/2018 – 08/2021
    M.Sc. in Medical Engineering at Friedrich-Alexander-Universität Erlangen-Nürnberg
    Thesis: “Towards Low-Dose Contrast-Enhanced Cardiac Magnetic Resonance Imaging Using Deep Learning”, written at Siemens Healthineers (Magnetic Resonance), Erlangen
  • 10/2014 – 10/2018
    B.Sc. in Medical Engineering at Friedrich-Alexander-Universität Erlangen-Nürnberg
    Thesis: “Automatic Stitching of Retina-Panoramas Using Single Frames from a Smartphone-Mounted Ophthalmoscope”, written at Fraunhofer IIS, Erlangen


  • Seminar: Machine Learning in MRI (WS/SS)
  • Exercise: Medizintechnik II (Bildgebende Verfahren) (SS)



Conference Contributions


Journal Articles

Conference Contributions


Conference Contributions


Journal Articles


Journal Articles

Student Projects and Theses

Student Title Type Status
Erik Stein Inline Implementation of Low-Latency Reconstruction for Real-Time Cardiac Cine MRI Using FIRE Project Running
Maximilian Riehl Model-based Deep Learning Reconstruction of Cardiac T1 and T2 mapping Master’s Thesis Running
Yannik Ott Deep Learning-Based Reconstruction of Radial Real-time Cine MRI Using Image-Based and k-Space-Based Methods Master’s Thesis Running
Florian Fürnrohr Zero-shot Learning Reconstruction for 3D MR Angiography Master’s Thesis Running
Yannik Ott Domain-Adaptive Heatmap Regression for Landmark Detection in Cardiac MRI Project Finished
Navaneeth Narayanan Low-field MRI Reconstruction Using the M4Raw Dataset and Investigating the Domain Gap Between fastMRI and M4Raw Datasets Project Finished
Maximilian Riehl Time-Resolved Coil Profiles for Dynamic MRI Reconstruction Project Finished
Karlo Fonseca Test-Time Training for Reconstruction of Low-field MRI Project Finished
Arpita Halder Self-supervised Learning for MRI Reconstruction of Cardiac Cine MRI Using VORTEX Project Finished
Daniel Amsel End-to-End Deep Learning-Based Reconstruction of Accelerated T1 Mapping for Cardiac MRI Master’s Thesis Finished
Lucas Lemos Franco / Lukas Bolay Score-Based Diffusion Models for Accelerated MRI Reconstruction Project Finished
Daniel Amsel Motion-Informed Cardiac Cine MRI Reconstruction Using a Variational Network and Voxelmorph Project Finished
Ute Spiske Deep Learning-Based Scar Quantification on Contrast-Enhanced Cardiac MRI Master’s Thesis Finished
Ute Spiske Evaluation of U-Net for Scar Segmentation on Late Gadolinium Enhancement Cardiac MR Images Research Laboratory Finished