Marc Vornehm
Marc Vornehm, M. Sc.
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
Teaching
- Seminar: Machine Learning in MRI (WS/SS)
- Exercise: Medizintechnik II (Bildgebende Verfahren) (SS)
Publications
2024
Conference Contributions
Data Consistent Variational Networks for Zero-shot Self-supervised MR Reconstruction
Bildverarbeitung für die Medizin 2024 (Erlangen, 10. March 2024 - 12. March 2024)
In: Andreas Maier, Thomas M. Deserno, Heinz Handels, Klaus Maier-Hein, Christoph Palm, Thomas Tolxdorff (ed.): Bildverarbeitung für die Medizin 2024, Wiesbaden: 2024
DOI: 10.1007/978-3-658-44037-4_81
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2023
Journal Articles
Dose reduction in sequence scanning 4D CT imaging through respiratory signal-guided tube current modulation: A feasibility study
In: Medical Physics 50 (2023), p. 7539-7547
ISSN: 0094-2405
DOI: 10.1002/mp.16785
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Conference Contributions
Dose reduction for respiratory signal-guided step-and-shoot 4DCT by online dose modulation
ESTRO 2023 (Vienna, 12. May 2023 - 16. May 2023)
In: Radiotherapy and Oncology 2023
DOI: 10.1016/S0167-8140(23)08960-0
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Deep learning-based accelerated T1 mapping for cardiac MRI
25. Jahrestagung der Deutschen Sektion der ISMRM (Berlin, 6. September 2023 - 7. September 2023)
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Deep Learning-Based Reconstruction of Accelerated Cardiac Cine MRI at 0.55T
2023 ISMRM & ISMRT Annual Meeting & Exhibition (Toronto, ON, 3. June 2023 - 8. June 2023)
In: Proceedings of the International Society for Magnetic Resonance in Medicine 2023
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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
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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
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Towards Low-Latency Deep Learning-Based Reconstruction of Real-Time Cine MRI
25. Jahrestagung der Deutschen Sektion der ISMRM (Berlin, 6. September 2023 - 7. September 2023)
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2022
Conference Contributions
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
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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 International Society for Magnetic Resonance in Medicine 2022
URL: https://index.mirasmart.com/ISMRM2022/PDFfiles/1014.html
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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
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2021
Journal Articles
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
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2020
Journal Articles
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
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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 |