Fluorescence Microscopy

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Software and Systems for Microbiology and Life Science

Background

Many experiments in microbiology, virology, immunology and “life science“ require a microscope based analysis of fluorescence image data. This often includes the investigation and combination of different sources of image information, such as bright field and phase contrast data as well as information from multiple fluorescence image channels.

Reviewing and interpreting such image data still is a labor and time consuming manual process which often results in a subjective or biased interpretation of the data with low reproducibility. Available software solutions can support researchers with the automated analysis of their data, but lots of practicing and expert knowledge in image processing are required to develop an image analysis workflow for a specific experiment.

Our Approach

In the context of the collaborative research center SFB 796 “Reprogramming of Host Cells by Microbial Effectors“ in Sub Project A4, we carry out research on novel image segmentation and image analysis tools applicable for multi-channel fluorescence image data. Our technology allows automatic training of an image analysis workflow based on hand-labeled data. The developed system can be adapted to new image data without requiring the manual adjustment of parameters using standard input devices (e. g. mouse, touchscreen, tablet computer). Based on the hand-labeled data, parameterization of the segmentation workflow is automatically calibrated by mathematical optimization techniques. As a result of this, manual parameter tuning is not required.

Our Proposal

We appreciate to offer services including feasibility studies as well as image based data analysis for your specific experiment. Besides adaption and licensing of existent algorithms, the implementation of custom algorithms and user interfaces is also possible. In addition to this, we offer support for the accreditation of medical devices and carry out research and development projects.

Literature

  • Held, C.; Palmisano, R.; Wenzel, J.; Lang, R.; Wittenberg, T.:. Segmentierung von Makrophagen in Fluoreszenzbildern mittels Fast Marching Level Set Verfahren. In: H. Handels et al (Hrsg.), Bildverarbeitung für die Medizin 2011, S. 129-133. Workshop, 20.-22.3.2011 in Lübeck, Springer Verlag, Heidelberg, 2011.
  • Wenzel, J.; Held, C.; Palmisano, R.; Teufel, S.; David, J. P.; Wittenberg, T.; Lang, R.: Measurement of TLR induced macrophage spreading by automated image analysis: differential role of Myd88 and MAPK in early and late responses. Frontiers in Systems Physiology, 2(71), 2011. doi: 0.3389/fphys.2011.00071.
  • Webel, R., Milbradt,J.; Auerochs, S.; Schregel, V.; Held, C.; Nöbauer, K.; Razzazi-Fazeli, E.; Jardin, C.; Wittenberg, T.; Sticht, H.; Marschall, M.: Two isoforms of the protein kinase pUL97 of human cytomegalovirus are differentially regulated in their nuclear translocalization. J. of General Virology, 92(3): 638-49, 2011.

Further Information

 

Certificate

Certified to ISO 13485

Brochure

Medical Image Processing