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4D imaging modalities offer powerful insights into developmental biology, at the expense of the generation of large, bulky datasets. The imaging compromises made when obtaining such datasets may result in less-than-desired frame rates or a reduction in signal quality particularly in highly dynamic developmental environments like that of the blastula stage zebrafish embryo. Existing software solutions though powerful either come at great cost or require large amounts of memory to be used effectively. Here, we present the protocol for using our own open-source, lightweight segmentation and tracking tool, sme.py, designed with fast-moving and dividing cells in mind. This software is designed to segment and track moving and dividing nuclei and their progeny in three dimensions and to record the cell cycle lengths of cell lineages.

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Image Segmentation Software for Nuclear Segmentation and Cell Cycle Tracking from 4D Embryo Light Sheet Data

  • 实验方案

  • 发表日期：

    2025年

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  • Haseeb Khalid Qureshi,
  • Andor Magony,
  • Yavor Hadzhiev,
  • Kacper Wozniak,
  • Attila Sík,
  • Ferenc Müller

摘要

4D imaging modalities offer powerful insights into developmental biology, at the expense of the generation of large, bulky datasets. The imaging compromises made when obtaining such datasets may result in less-than-desired frame rates or a reduction in signal quality particularly in highly dynamic developmental environments like that of the blastula stage zebrafish embryo. Existing software solutions though powerful either come at great cost or require large amounts of memory to be used effectively. Here, we present the protocol for using our own open-source, lightweight segmentation and tracking tool, sme.py, designed with fast-moving and dividing cells in mind. This software is designed to segment and track moving and dividing nuclei and their progeny in three dimensions and to record the cell cycle lengths of cell lineages.