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Segmentation of Cells from Spinning Disk Confocal Images Using a Multi-stage Approach

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Book cover Computer Vision -- ACCV 2014 (ACCV 2014)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9005))

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Abstract

Live cell imaging in 3D platforms is a highly informative approach to visualize cell function and it is becoming more commonly used for understanding cell behavior. Since these experiments typically generate large data sets their analysis manually would be very laborious and error prone. This has led to the necessity of automatic image analysis tools. Cell segmentation is an essential initial step for any detailed automatic quantitative analysis. When the images are captured from the 3D culture containing proliferating and moving cells, cell-cell interactions and collisions cannot be avoided. In these conditions the segmentation of individual cells becomes very challenging. Here we present a method which utilizes the edge probability map and graph cuts to detect and segment individual cells from cell clusters. The main advantage of our method is that it is capable of handling complex cell shapes because it does not make any assumptions about the cell shape.

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Author information

Authors and Affiliations

  1. Center for Machine Vision Research, University of Oulu, Oulu, Finland

    Saad Ullah Akram, Juho Kannala & Janne Heikkilä

  2. Biocenter Oulu, University of Oulu, Oulu, Finland

    Saad Ullah Akram, Mika Kaakinen & Lauri Eklund

  3. Faculty of Biochemistry and Molecular Medicine, University of Oulu, Oulu, Finland

    Mika Kaakinen & Lauri Eklund

Authors
  1. Saad Ullah Akram
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  2. Juho Kannala
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  3. Mika Kaakinen
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  4. Lauri Eklund
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  5. Janne Heikkilä
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Corresponding author

Correspondence to Saad Ullah Akram .

Editor information

Editors and Affiliations

  1. Technische Universität München, Garching, Bayern, Germany

    Daniel Cremers

  2. University of Adelaide, Adelaide, South Australia, Australia

    Ian Reid

  3. Keio University, Yokohama, Kanagawa, Japan

    Hideo Saito

  4. University of California at Merced, Merced, California, USA

    Ming-Hsuan Yang

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© 2015 Springer International Publishing Switzerland

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Akram, S.U., Kannala, J., Kaakinen, M., Eklund, L., Heikkilä, J. (2015). Segmentation of Cells from Spinning Disk Confocal Images Using a Multi-stage Approach. In: Cremers, D., Reid, I., Saito, H., Yang, MH. (eds) Computer Vision -- ACCV 2014. ACCV 2014. Lecture Notes in Computer Science(), vol 9005. Springer, Cham. https://doi.org/10.1007/978-3-319-16811-1_20

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  • DOI: https://doi.org/10.1007/978-3-319-16811-1_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-16810-4

  • Online ISBN: 978-3-319-16811-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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