Mission Statement

“Improve the understanding of diseases and their diagnosis through the automated analysis and quantification of microscopy images”

— Marina Zimmermann, PhD

Team Members

PhD student

Nico Kaiser


The Group of Computational Pathology develops algorithms to analyse medical images, in particular microscopy images, in order to improve clinical diagnoses and advance the understanding of diseases. One of the focuses of our work is the quantitative analysis and discovery of signatures of diseases based on the segmentation of microscopy images with deep learning and classical image processing techniques. In order to achieve these goals, we collaborate closely with other groups at the HCKH and the UKE.

Marina Zimmermann, PhD

Assistant Professor 

Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-Eppendorf (UKE)
Falkenried 94
20251 Hamburg, Germany


Current Position
since 2023 Assistant Professor for Computational Pathology, Institute of Medical Systems Biology (IMSB)
University Training
 2011 - 2013

M.Sc. in Electrical and Electronics Engineering, Ecole polytechnique fédérale de Lausanne (EPFL), Switzerland

 2008 - 2011 B.Sc. in Electrical and Computer Engineering, Jacobs University Bremen, Germany
Academic qualifications
2014 - 2018- 2020

PhD in Electrical Engineering, Signal Processing Laboratory 5, Ecole polytechnique fédérale de Lausanne (EPFL), Switzerland, Supervisor: Prof. Jean-Philippe Thiran

Previous professional career

Scientific postgraduate education:

2021 - 2023 Team lead, Computational Pathology at Institute of Medical Systems Biology (IMSB), University Medical Center Hamburg-Eppendorf (UKE), Germany
2018 - 2023

Postdoctoral researcher, Institute of Medical Systems Biology (IMSB) and III. Department of Medicine, University Medical Center Hamburg-Eppendorf (UKE), Germany

2013 - 2018

Research assistant, Signal Processing Laboratory 5, Ecole polytechnique fédérale de Lausanne (EPFL), Switzerland

Selected publications

Kylies D, Zimmermann M, Haas F, Schwerk M, Kuehl M, Brehler M, Czogalla J, Hernandez L, Konczalla L, Okabayashi Y, Menzel J, Edenhofer I, Mezher S, Aypek H, Dumoulin B, Wu H , Hofmann S, Kretz O, Wanner N, Tomas N, Krasemann S, Glatzel M, Kuppe C, Kramann R, Benjamin B, Schneider R, Urbschat C, Arck P, Gagliani N, Wiech T, Grahammer F, Saez P, Wong MN, Bonn S, Huber TB, Puelles, VG.  Nat Nanotechnol. 2023 Apr;18(4):336-342.
Ragab H, Westhaeusser F, Ernst A, Yamamura J, Fuhlert P, Zimmermann M, Sauerbeck J, Shenas F, Özden C, Weidmann A, Adam G, Bonn S, Schramm C. Radiol Artif Intell. 2023 Apr 19;5(3):e220160.

Deep learning-based molecular morphometrics for kidney biopsies.
Zimmermann M*, Klaus M*, Wong MN, Thebille AK, Gernhold L, Kuppe C, Halder M, Kranz J, Wanner N, Braun F, Wulf S, Wiech T, Panzer U, Krebs CF, Hoxha E, Kramann R, Huber TB*, Bonn S*, Puelles VG*. JCI Insight. 2021 Apr 8;6(7):e144779. 

Thebille AK, Dietrich E, Klaus M, Gernhold L, Lennartz M, Kuppe C, Kramann R, Huber TB, Sauter G, Puelles VG, Zimmermann M*, Bonn S*. Annual Conference on Medical Image Understanding and Analysis 2021.

Towards Explainable End-to-End Prostate Cancer Relapse Prediction from H&E Images Combining Self-Attention Multiple Instance Learning with a Recurrent Neural Network.
Dietrich E, Fuhlert P, Ernst A, Sauter G, Lennartz M, Stiehl HS, Zimmermann M*, Bonn S*. Machine Learning for Health 2021.

* Represents equal contributions as co-first or co-senior authors.



November 2023 | News

Great success for kidney research at the UKE: Approval of the third funding period of the SFB 1192

The Collaborative Research Center (SFB) 1192 "Immune-Mediated Glomerular Diseases" of the ...

November 28, 2023 | Lecture, Prof. Dr. Ulf Panzer

Role of T cells and cytokines in (renal) autoimmunity

August 2023 | New Publication

An integrated organoid omics map extends modeling potential of kidney disease

UKE Paper of the Month (PoM) September 2023 

Martinistraße 52
Campus Research N27
20246 Hamburg Germany
This email address is being protected from spambots. You need JavaScript enabled to view it.

University Medical Center Hamburg - Eppendorf