PhD Candidate
E-mail: N [dot] Hampe [at] amsterdamumc [dot] nl
Phone: +31 20 56 65206


Nils Hampe received his Bachelor degree in Physics at the Karlsruhe Institute of Technology, Germany. Seeking for more practically applicable challenges he enrolled in the Master course Biomedical Engineering at the University of Lubeck, Germany, which he finished with honours in 2019. His Master thesis emerged from a collaboration with Philips Research Hamburg and UMC Utrecht under the title “Deep learning for Electrical Properties Tomography”. In 2019, Nils became a PhD candidate at the Quantitative Medical Image Analysis Group (Image Sciences Institute) under supervision of Dr. Ivana Isgum. His research focuses on artificial intelligence for cardiovascular risk assessment.


Journal Articles

1.

N. Hampe, U. Katscher, C.A.T. van den Berg, K.K. Tha, S. Mandija

Investigating the challenges and generalizability of deep learning brain conductivity mapping Journal Article

Physics in Medicine & Biology, 65 (13), pp. 135001, 2020.

Abstract | Links | BibTeX

2.

N. Hampe, J.M. Wolterink, S.G.M. van Velzen, T. Leiner, I. Išgum

Machine learning for assessment of coronary artery disease in cardiac CT: a survey Journal Article

Frontiers in Cardiovascular Medicine, 6 (172), 2019.

Abstract | Links | BibTeX

Inproceedings

1.

N. Hampe, J.M. Wolterink, C. Collet, R.N. Planken, I. Išgum

Graph Attention Networks for Segment Labeling in Coronary Artery Trees Inproceedings

In: SPIE Medical Imaging, pp. 115961I, 2021.

Abstract | Links | BibTeX

2.

M. Zreik, N. Hampe, T. Leiner, N. Khalili, J.M. Wolterink, M. Voskuil, M.A. Viergever, I. Išgum

Combined analysis of coronary arteries and the left ventricular myocardium in cardiac CT angiography for detection of patients with functionally significant stenosis Inproceedings

In: SPIE Medical Imaging, pp. 115961F, 2021.

Abstract | Links | BibTeX