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 Email: firstname.lastname@tum.de Phone: 089 4140 9101 Google Scholar Linkedin Twitter

About

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.

Publications

2021
	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. (bib)
2020
	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. (bib)
	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. (bib)
	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)
2019
	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)