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You come up with an idea and want to back it up with quantitative data from microscopic images? Contact us!

The Core Facility Image Analysis supports researchers from biomedicine with their rich experience on classical Image Processing and Pattern Recognition as well as latest Deep Learning techniques for solving image analysis problems from various image sources. With this we try to bridge the gap between biology, medicine and computer science.


As part of the Microscopy and Image Analysis Platform (MIAP) we provide training to solve frequent image analysis tasks using classical image processing techniques but also recent learning-based approaches. Check the MIAP homepage for upcoming workshops and events.


Support

Our team of experts in Image Processing, Pattern Recognition and Machine Learning can help you with many important decisions when designing your experiments towards full exploitation of microscopic image data. Ideally you already have some preliminary images we can look at to discuss your options, ranging from pointing you to the right tool, giving you ideas on how to optimize your imaging settings for automated image analysis or accompanying you the long way from idea to final publication with custom made solutions.

Teaching

The Core Facility Image Analysis offers insights into basic principles of Image Analysis and example applications in undergraduate courses for Bachelor and Master students in biology in the module Engineering meets Biology and the profile module Quantitative Methods - Translational Biology. We provide workshops for PhD students and Postdocs within the MIAP network.

Research

Our close cooperation with the Computer Vision lab headed by Prof. Dr. Thomas Brox allows us to provide tools from bleading edge research as service to the biomedical community.

Software

We aim at making software solutions available that allow on-site Image Analysis within popular frameworks like ImageJ or KNIME. We offer developed software free of charge with open source license and if possible also in binary form for common operating systems. We also try to provide intuitive user interfaces.

News:

ISOO-DL v2 has been accepted at ISBI. Congratulations to Anton! (December 2018)
U-Net for everyone. Our U-Net Segmentation plugin for Fiji is now officially released. See our Nature Methods brief communication for more details (December 2018)
ISOO-DL overlapping instance segmentation article accepted at ISBI. Congratulations to Anton! (December 2017)
Congratulations to Robert and Dominic for their PhD! We wish you all the best for your future and hope we stay in touch! (December 2017)
Robert left the group and moved to Munich. (October 2017)
A warm welcome to Yassine who will work on advanced Deep Learning techniques for biomedical image analysis. (October 2017)
Dominic left the group. (July 2017)
Tobacco Root Article accepted at The Plant Journal (June 2017)
Microglia Article published in Nature Neuroscience (May 2017)
Congratulations to Dominic!
Anomaly Detection Article published in International Journal of Computer Vision (IJCV) (April 2017)
Congratulations to Robert!
3-D U-Net Article presented at Medical Image Computing and Computer-Assisted Intervention (MICCAI) (October 2016)
Congratulations to Özgün!
We warmly welcome Anton who will work on the ZIM Project "Smart Process Inspection" (August 2016)

Ongoing Projects

BIOSS Logo

BIOSS     Centre or Biological Signalling Studies

Area Z4 - Image Analysis
Cluster of Excellence founded by the DFG (EXC 294)

KIDGEM Logo

KIDGEM     Kidney Disease - From Genes to Mechanisms

Area Z2 - Image Analysis
Collaborative Research Center founded by the DFG (SFB 1140)

Smart Process Inspection (SPI)

Smart Process Inspection "SPI"     At line und in situ Mehrparameteranalyse mittels foto- und elektrooptischer Messtechnik; Entwicklung von Methoden des Deep Learning zur Detektion, Verfolgung und quantitativen Beschreibung von Partikeln in der Bioprozessanalyse

Founded by the German Ministry for Economical Affairs and Energy (BMWi Fkz.: ZF4184101)

Finished Projects

Microsystems Logo

Microsystems     BioSystemanalyse von Mikrosporen zur Verbesserung der industriellen Embryoproduktion in Pflanzen

Founded by the German Ministry for Education and Research (BMBF Fkz.: 0316185)

Quantitative 3D and 4D cell analysis in living organisms - novel instrumentation, computational tools, proof of concept applications

Founded by the German Ministry for Education and Research