Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

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Johannes Paetzold


Johannes C. Paetzold
PhD candidate

Image-Based Biomedical Modeling Group (IBBM)
Fakultät für Informatik
Technische Universität München

Office: TranslaTUM Room No. 22.2.34

Phone: 089 4140 9101

Google Scholar


My name is Johannes, I am a third year PhD student in Machine Learning. My main interest is the development of deep learning and graph learning methods for large biological networks such as vessels and neurons. Most of the applications I work on concern Medical Imaging and Microscopy with some extension to Remote Sensing. Further research interests include topology aware machine learning and generative models. I also lead the AI Team at the Institute for Tissue Engineering and Regenerative Medicine(iTERM) at the Helmholtz Zentrum München.

Research Interests

  • Deep learning in Computer Vision.
  • Generative Models.
  • Graph Neural Networks.

Student Projects

We are inviting applications for several exciting research opportunities for Master students with our group. Please also feel free to reach out if you are interested in a Theses, research project, etc. The projects are intended for students in Informatics, Physics, Mathematics, Electrical Engineering, or related fields.


S. Shit, J. Paetzold, I. Ezhov, A. Sekuboyina, B. Menze
clDice - a Novel Connectivity-Preserving Loss Function for Vessel Segmentation
IEEE Conference on Computer Vision and Pattern Recognition, Nashville, Tennessee, United States, June 2021.
Shit and Paetzold share first authorship.
O. Gerl, J. Paetzold, , I. Ezhov, S. Shit, F. Kofler, , G. Tetteh, V. Ntziachristos, B. Menze
A distance-based loss for smooth and continuous skin layer segmentation in optoacoustic images.
International Conference on Medical Image Computing and Computer Assisted Intervention 2020 (MICCAI)
Gerl and Paetzold share first authorship.
M.I.Todorov, J. Paetzold, O. Schoppe, G. Tetteh, S. Shit, , B. Menze, A. Ertuerk
Machine learning analysis of whole mouse brain vasculature.
Nature Methods volume 17, pages 442 to 449, (2020).
Todorov and Paetzold share first authorship.
S. Zhao, M.I.Todorov, O. Schoppe, J. Paetzold, B. Menze, A. Ertuerk
Cellular and Molecular Probing of Intact Human Organs.
Cell Volume 180, Issue 4, Pages 796-812.e19 (bib)
J. Paetzold, S. Shit, I. Ezhov, G. Tetteh, A. Ertuerk, B. Menze
clDice-a Novel Connectivity-Preserving Loss Function for Vessel Segmentation
Medical Imaging Meets NeurIPS? 2019 (Workshop), Vancouver, Canada, December 2019. (bib)
F. Navarro, S. Shit, I. Ezhov, J. Paetzold, A. Gafita, J. Peeken, S. Combs, B. Menze
Shape-Aware Complementary-Task Learning for Multi-Organ Segmentation
Proceedings of the 10th International Workshop on Machine Learning in Medical Imaging (MLMI 2019), Shenzhen, China, October 2019. (bib)
H. Li, J. Paetzold, A. Sekuboyina, F. Kofler, Jianguo Zhang, J. Kirschke, B. Wiestler, B. Menze
DiamondGan: Unified Multi-modal Generative Adversarial Networks for MRI Sequences Synthesis
Proceedings of the 22th International Conference on Medical Image Computing and Computer Assisted Interventions (MICCAI), Shenzhen, China, October 2019. (bib)

Title: M.Sc.
Circumference of your head (in cm):  
Firstname: Johannes
Middlename: C.
Lastname: Paetzold
Nationality: Blank
Languages: English, German, French
Expertise: Segmentation, Medical Imaging, Computer Vision
Position: Scientific Staff
Status: Active
Emailbefore: firstname.lastname
Room: Translatum 22.2.34
Telephone: 089 4140 9101

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