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Focal Stacking for Crystallization Microscopy

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Data Analytics for Protein Crystallization

Part of the book series: Computational Biology ((COBO,volume 25))

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Abstract

Automated image analysis of protein crystallization images is one of the important research areas. For proper analysis of the microscopic images, it is necessary to have all objects in good focus. If objects in a scene (or specimen) appear at different depths with respect to the camera’s focal point, objects outside the depth of field usually appear blurred. Therefore, scientists capture a collection of images with different depths of field. Each of these images can have different objects in focus. Focal stacking is a technique of creating a single focused image from a stack of images collected with different depths of field. In this chapter, we analyze focal stacking techniques suitable for trace fluorescently labeled protein crystallization images but also applicable images captured under white light.

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Notes

  1. 1.

    Images obtained from http://bigwww.epfl.ch/demo/edf/demo_5.html (Courtesy of Peter Lundh von Leithner and Heba Ahmad, Institute of Ophthalmology, London).

  2. 2.

    http://www.textureking.com/content/img/stock/big/DSC_3518.JPG.

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Acknowledgements

\(\copyright \)2016 IEEE. Reprinted, with permission, from M. S. Sigdel, M. Sigdel, S. Dinç, I. Dinc, M. L. Pusey and R. S. Aygün, “FocusALL: Focal Stacking of Microscopic Images Using Modified Harris Corner Response Measure,” in IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 13, no. 2, pp. 326–340, March-April 1 2016. doi: https://doi.org/10.1109/TCBB.2015.2459685

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Authors and Affiliations

  1. iXpressGenes, Inc., Huntsville, AL, USA

    Marc L. Pusey

  2. University of Alabama in Huntsville, Huntsville, AL, USA

    Ramazan Savaş Aygün

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  1. Marc L. Pusey
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  2. Ramazan Savaş Aygün
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Correspondence to Marc L. Pusey .

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Pusey, M.L., Aygün, R.S. (2017). Focal Stacking for Crystallization Microscopy. In: Data Analytics for Protein Crystallization. Computational Biology, vol 25. Springer, Cham. https://doi.org/10.1007/978-3-319-58937-4_7

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  • DOI: https://doi.org/10.1007/978-3-319-58937-4_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-58936-7

  • Online ISBN: 978-3-319-58937-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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