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Efficient, interactive, and three-dimensional segmentation of cell nuclei in thick tissue sections

S J Lockett1, D Sudar, C T Thompson

  • 1Life Sciences Division, Ernest Orlando Lawrence Berkeley National Laboratory, Berkeley 94720, California, USA. sjlockett@lbl.gov

Cytometry
|April 29, 1998
PubMed
Summary

This study introduces a new interactive algorithm for segmenting cell nuclei in 3D images. It simplifies the process by requiring fewer user inputs, improving efficiency in biological research.

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Area of Science:

  • * Biology
  • * Image Analysis
  • * Microscopy

Background:

  • * Accurate segmentation of intact cell nuclei in 3D images is crucial for biological research.
  • * Automatic algorithms often fail to segment all nuclei in thick tissue sections, necessitating interactive methods.
  • * Current interactive methods are labor-intensive, requiring border delineation in every 2D plane of a 3D image.

Purpose of the Study:

  • * To develop a more efficient interactive algorithm for segmenting cell nuclei in 3D images.
  • * To reduce the user effort required for accurate nuclear segmentation in thick tissue sections.
  • * To improve the speed and accuracy of 3D cell nucleus segmentation for biological studies.

Main Methods:

  • * An interactive algorithm that requires users to draw nuclear borders only in central 2D planes where borders are most distinct.

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  • * The algorithm interpolates the entire nuclear surface from a minimal set of user-defined borders (five per nucleus).
  • * An optional automatic surface optimization step to refine the accuracy of the segmented nuclear surface.

    • Main Results:

    • * The algorithm successfully segments objects corresponding to individual, visually identifiable cell nuclei.
    • * User interaction is significantly reduced compared to existing methods that require delineation in all 2D planes.
    • * The segmented surfaces closely represent the true nuclear surface, with potential for further refinement.

    Conclusions:

    • * The developed algorithm offers a more efficient and user-friendly approach to 3D cell nucleus segmentation.
    • * This method enhances the feasibility of detailed nuclear analysis in complex biological samples.
    • * The algorithm provides a valuable tool for researchers requiring accurate segmentation of cell nuclei in 3D imaging studies.