Maximilian Reymann, M. Sc.
Researcher
Martensstr. 3
91058 Erlangen
Department of Computer Science
Chair of Computer Science 5 (Pattern Recognition)
Martensstr. 3
91058 Erlangen
- Phone number: +49 9131 85 28982
- Fax number: +49 9131 85 27270
- Email: maximilian.reymann@fau.de
- Website: https://lme.tf.fau.de/person/reymann/
Office hours
Each week Fr,- Since 04/2019:
PhD student at the Pattern Recognition Lab, Friedrich-Alexander-University Erlangen-Nürnberg (FAU), Germany
In cooperation with Siemens Medical Solutions, Hoffman Estates, USA and Clinic of Nuclear Medicine, University Hospital Erlangen, Germany - Until 03/2019:
Masters degree in Medical Engineering with focus on Image and Data Analytics at the FAU - Until 09/2016:
Bachelors degree in Medical Engineering with focus on Prosthetics at the FAU - 03/2016 – 09/2016:
Bachelor’s thesis at the computational Cardiology Lab, Johns Hopkins University, Baltimore, USA
2019
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Improving multi-modal quantitative SPECT with Deep Learning approaches to optimize image reconstruction and extraction of medical information
(Non-FAU Project)
Term: April 1, 2019 - April 30, 2022This project aims to improve multi-modal quantitative SPECT with Deep Learning approaches to optimize image reconstruction and extraction of medical information. Such improvements include noise reduction and artifact removal from data acquired in SPECT.
2019
Conference Contributions
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Deep Image Denoising in SPECT
Annual Congress of the European Association of Nuclear Medicine (Barcelona, October 12, 2019 - October 16, 2019)
In: Springer-Verlag GmbH Germany, part of Springer Nature 2019 (ed.): European Journal of Nuclear Medicine and Molecular Imaging (2019) 46 (Suppl 1): S1–S952, 10.1007/s00259-019-04486-2, Berlin, Heidelberg: 2019
DOI: 10.1007/s00259-019-04486-2
URL: https://link.springer.com/article/10.1007/s00259-019-04486-2
BibTeX: Download - , , , , , , :
U-Net for SPECT Image Denoising
2019 IEEE Nuclear Science Symposium (NSS) and Medical Imaging Conference (MIC) (Manchester, October 26, 2019 - November 2, 2019)
In: IEEE (ed.): 2019 IEEE Nuclear Science Symposium and Medical Imaging Conference Proceedings (NSS/MIC) 2019
BibTeX: Download
2016
Conference Contributions
- , , , , , :
Blood glucose level prediction based on support vector regression using mobile platforms
38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (Orlando, Florida, USA, August 16, 2016 - August 19, 2016)
In: 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) 2016
DOI: 10.1109/EMBC.2016.7591358
URL: https://www.mad.tf.fau.de/files/2017/06/2016-Reymann-EMBC-BGL.pdf
BibTeX: Download
| Type | Title | Status |
|---|---|---|
| Project | Deep Learning based Model Observers for Multi-modal Imaging | finished |
| MA thesis | Disentanglement Learning for Processing Medical Images | running |
| Project | Analysis of NVIDIA Optix Engine for Ray Tracing in SPECT | running |
| Project | GAN Generated Model Observer for one Class Detection in SPECT Imaging | running |
| Project | Adapting Pyro-NN with SPECT operators | finished |
| Project | Advancing the digital twin method | finished |
| BA thesis | Improved image quality of Limited Angle and Sparse View SPECT using Deep Learning | finished |
| MA thesis | Synthetic generation of CT image from non-attenuation corrected FDG-PET image using GANs and its application to whole-body PET/CT registration. | running |
| MA thesis | Convolutional Neural Networks for multi-organ segmentation of SPECT projections | finished |