Skip to main content

Image Preprocessing Pipeline for Bright-Field Miniature Live Cell Microscopy Prototypes

  • Conference paper
  • First Online:
Book cover International Multidisciplinary Microscopy Congress

Part of the book series: Springer Proceedings in Physics ((SPPHY,volume 154))

  • 1094 Accesses

Abstract

One of the biggest technical challenges in live cell imaging is to keep the cells in a healthy state while imaging them. In fact, being able to observe living cells in their cultivation environment over time is a major step to understand and diagnose diseases. For this purpose, we are using a novel microscopic system composed of microscopy prototypes that can, in contrast to most available live cell microscopes, operate in an incubator. Each prototype observes one well of a 24 well plate over time. The in-incubator operability imposes manufacturing constraints on the size of our microscopic system and consequently degrades the delivered image quality. In order to get usable live cell images with the prototypes, a preprocessing pipeline was introduced. First, the exposure time is increased until the circular illumination is visible. Second, the illumination field is estimated using Gaussian smoothing and the center of the circular illumination is detected. Third, based on the illumination center, a 1 mm\(^{2}\) region is cropped. Fourth, using the resulting image’s standard deviation, a suitable exposure time is found in order to avoid under- or over-exposure. Finally, the illumination is corrected by subtracting the estimated illumination field and the image contrast is stretched. The prototypes and the pipeline are currently in use at the laboratory of our bioprocess engineering partners. The generated images and videos enable them to analyse the behavior of cells over time.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. R.Y. Tsien, Imagining imaging’s future. Nat. Rev. Mol. Cell Biol. 4 (Suppl), SS16–21 (2003)

    Google Scholar 

  2. Q. Wu, F.A. Merchant, K.R. Castleman, Microscope Image Processing (Academic Press, Massachusetts, 2008)

    Google Scholar 

  3. D. Gerlich, J. Ellenberg, 4D imaging to assay complex dynamics in live specimens. Nat. Cell Biol. 5(Suppl), 14–19 (2003)

    Google Scholar 

  4. Y. Ohno, Photometric calibrations. Natl. Inst. Stand. Technol. Spec. Publ. (1997). http://www.nist.gov/manuscript-publication-search.cfm?pub_id=104697

  5. Y. Sun, S. Duthaler, B.J. Nelson, Autofocusing in computer microscopy: selecting the optimal focus algorithm. Microsc. Res. Tech. 65, 139–149 (2004)

    Article  Google Scholar 

  6. T.T.E. Yeo, S.H. Ong, R. Jayasooriah, Sinniah, Autofocusing for tissue microscopy. Image Vision Comput. 11, 629–639 (1993)

    Google Scholar 

  7. F. Mualla, S. Schöll, B. Sommerfeldt, A. Maier, J. Hornegger, Automatic cell detection in bright-field microscope images using SIFT, random forests, and hierarchical clustering. IEEE Trans. Med. Imag. 32, 2274–2286 (2013)

    Google Scholar 

  8. F. Mualla, S. Schöll, B. Sommerfeldt, J. Hornegger, Using the Monogenic Signal for Cell-Background Classification in Bright-Field Microscope Images, Proceedings des Workshops Bildverarbeitung für die Medizin 2013. (Springer, Heidelberg, 2013), pp. 170–174

    Google Scholar 

  9. R. Ali, M. Gooding, T. Szilágyi, B. Vojnovic, M. Christlieb, M. Brady, Automatic segmentation of adherent biological cell boundaries and nuclei from brightfield microscopy images. Mach. Vision Appl. 23, 607–621 (2012)

    Google Scholar 

Download references

Acknowledgments

The authors would like to thank the Bavarian Research Foundation BFS for funding the project COSIR under contract number AZ-917-10 and the industrial partners for the productive collaboration. Furthermore the authors gratefully acknowledge funding of the Erlangen Graduate School in Advanced Optical Technologies (SAOT) by the German Research Foundation (DFG) in the framework of the German excellence initiative.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to S. Schöll .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Schöll, S., Mualla, F., Sommerfeldt, B., Steidl, S., Maier, A. (2014). Image Preprocessing Pipeline for Bright-Field Miniature Live Cell Microscopy Prototypes. In: Polychroniadis, E., Oral, A., Ozer, M. (eds) International Multidisciplinary Microscopy Congress. Springer Proceedings in Physics, vol 154. Springer, Cham. https://doi.org/10.1007/978-3-319-04639-6_37

Download citation

Publish with us

Policies and ethics