Erik Gösche
Erik Gösche, M. Sc.
I am specializing in the development of deep learning algorithms for MRI reconstruction. My research focuses on creating advanced techniques to improve the quality and usability of dynamic contrast-enhanced MRI (DCE-MRI) for breast imaging.
I am happy to supervise motivated students for a project or thesis who have already gained first experience in the field of MRI reconstruction. Feel free to contact me!
- Since 02/2024
Ph.D. Candidate at Computational Imaging Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg - 10/2021 – 11/2023
M.Sc. in Data Science at Friedrich-Alexander-Universität Erlangen-Nürnberg
Thesis: “Attention-based networks for brain segmentation in k-space”, written at University of California, San Francisco - 10/2018 – 09/2021
B.Sc. in Applied Computer Science at University of Applied Sciences Mittweida
Thesis: “Object detection as a pre-processing step for segmentation of people”, written at Volkswagen Sachsen GmbH, Zwickau
- Seminar: Machine Learning in MRI (WS/SS)
2024
Conference Contributions
Domain Influence in MRI Medical Image Segmentation: Spatial Versus k-Space Inputs
15th International Workshop on Machine Learning in Medical Imaging, Held in Conjunction with MICCAI 2024 (Marrakesh, 6. October 2024 - 6. October 2024)
In: Xuanang Xu, Zhiming Cui, Islem Rekik, Xi Ouyang, Kaicong Sun (ed.): Machine Learning in Medical Imaging, Cham: 2024
DOI: 10.1007/978-3-031-73284-3_31
URL: https://link.springer.com/chapter/10.1007/978-3-031-73284-3_31
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Student | Title | Type | Status |
Nguyen Anh Mai | Extension and Evaluation of the SPICER Architecture for 2D+Time Cardiovascular MRI Reconstruction | Project | Running |
Ximeng Zhang | Comparative Literature Review of DCE MRI Analysis Frameworks and Tracer Kinetic Modeling Approaches | Master’s Thesis | Running |
Alen Jose Anto | Comparison of non-uniform Fast Fourier Transform implementations using DCE MRI data | Project | Completed |