Marc Vornehm

Marc Vornehm, M. Sc.

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

Room 2.01
Werner-von-Siemens Str. 61
91052 Erlangen

Email: marc.vornehm@fau.de
Website: https://www.cil.tf.fau.de/person/vornehm/

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.

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

Furthermore, I am an elected doctoral candidates’ representative at the Faculty of Engineering. More information can be found here.

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

Teaching

Seminar: Machine Learning in MRI
Exercise: Medizintechnik II (Bildgebende Verfahren)

Publications

2023

Vornehm M., Spiske U., Fenski M., Wetzl J., Preuhs E., Maier A., Schulz-Menger J., Giese D.:
Fully Automatic Scar Segmentation on LGE Images with Reduced Contrast Agent Dose
SCMR 26th Annual Scientific Sessions (San Diego, CA, 25. January 2023 - 28. January 2023)
In: Proceedings of the SCMR 26th Annual Scientific Sessions 2023
Vornehm M., Wetzl J., Giese D., Knoll F.:
k-t Adaptive Regularization in Variational Networks for Cardiac Cine Reconstruction
ISMRM Workshop on Data Sampling & Image Reconstruction (Sedona, AZ, 8. January 2023 - 11. January 2023)
In: Proceedings of the ISMRM Workshop on Data Sampling & Image Reconstruction 2023

2022

Vornehm M., Fenski M., Preuhs E., Maier A., Schulz-Menger J., Wetzl J., Giese D.:
Improving the Sensitivity to Myocardial Scar in Automatic Segmentations of Left Ventricular Myocardium on LGE Images
Joint Annual Meeting ISMRM-ESMRMB & ISMRT 31st Annual Meeting (London, 7. May 2022 - 12. May 2022)
In: Proceedings of the Joint Annual Meeting ISMRM-ESMRMB 2022 & ISMRT Annual Meeting 2022
URL: https://index.mirasmart.com/ISMRM2022/PDFfiles/1014.html
Vornehm M., Fenski M., Preuhs E., Maier A., Schulz-Menger J., Wetzl J., Giese D.:
Myocardial scar segmentation on cardiac LGE images with reduced contrast agent dose using deep learning
24. Jahrestagung der Deutschen Sektion der ISMRM (Aachen, 21. September 2022 - 24. September 2022)
In: Abstractband der 24. Jahrestagung der Deutschen Sektion der ISMRM 2022
Vornehm M., Wetzl J., Giese D., Ahmad R., Knoll F.:
Spatiotemporal variational neural network for reconstruction of highly accelerated cardiac cine MRI
Artificial Intelligence in Cardiovascular Magnetic Resonance Imaging - A Joint Summit of the EACVI and SCMR (London, 5. May 2022 - 6. May 2022)
In: European Heart Journal - Cardiovascular Imaging 2022
DOI: 10.1093/ehjci/jeac141.018

2021

Werner R., Szkitsak J., Sentker T., Madesta F., Schwarz A., Fernolendt S., Vornehm M., Gauer T., Bert C., Hofmann C.:
Comparison of intelligent 4D CT sequence scanning and conventional spiral 4D CT: A first comprehensive phantom study
In: Physics in Medicine and Biology 66 (2021), Article No.: 015004
ISSN: 0031-9155
DOI: 10.1088/1361-6560/abc93a

2020

Werner R., Sentker T., Madesta F., Schwarz A., Vornehm M., Gauer T., Hofmann C.:
Intelligent 4D CT sequence scanning (i4DCT): First scanner prototype implementation and phantom measurements of automated breathing signal-guided 4D CT
In: Medical Physics 47 (2020), p. 2408-2412
ISSN: 0094-2405
DOI: 10.1002/mp.14106

Student theses and projects

Student	Title	Type	Status
Florian Fürnrohr	Zero-shot Learning Reconstruction for 3D MR Angiography	Master’s Thesis	Running
Daniel Amsel	End-to-end Deep Learning-Based Reconstruction of Accelerated T1 Mapping for Cardiac MRI	Master’s Thesis	Running
Ute Spiske	Deep Learning-Based Scar Quantification on Contrast-Enhanced Cardiac MRI	Master’s Thesis	Finished