Erik Gösche
Professorship for Computational Imaging
Research associates
Contact
Office hours
by appointment
Research field
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 theses who have already gained first experience in the field of MRI reconstruction. Please note that applications will only be considered if submitted through the application form on our website.
- 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
- Computational Complexity Exercise (WiSe)
- Medizintechnik II Tafelübung (SoSe)
- Seminar: Machine Learning in MRI (WiSe/SoSe)
2025
Conference Contributions
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Comparative Evaluation of Deep Learning and Compressed Sensing Methods for Dynamic Contrast-Enhanced MRI Reconstruction
2025 ISMRM & ISMRT Annual Meeting & Exhibition (Honolulu, HI, 10. May 2025 – 15. May 2025) - , , , , , , :
Direct Reconstruction of Tracer Kinetic Parameter Maps in Abbreviated Breast MRI
2025 ISMRM & ISMRT Annual Meeting & Exhibition (Honolulu, HI, 10. May 2025 – 15. May 2025)
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
- Shengyang Wu, Master’s thesis, ongoing
- Philip Pentzel, Bachelor’s thesis, ongoing
- Rahul Sawhney, Project, ongoing
- Alen Jose Anto, Master’s thesis, 2025
- Christopher Brückner, Master’s thesis, 2025
- Nguyen Anh Mai, Project, 2025
- Ximeng Zhang, Master’s thesis, 2024
- Alen Jose Anto, Project, 2024