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. 2024 Nov 22;4:e14. doi: 10.1017/S2633903X24000114

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© The Author(s) 2024

This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.

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Figure 2. — Case Study 2: Three-dimensional (3D) nuclei segmentation: Pipeline and data set. The data set consists of two distinct embryos, labeled 01 and 02. One embryo is used for fine-tuning the StarDist network in ZeroCostDL4Mic, following downsampling and noise filtering, whereas the other is utilized for inference. After training the StarDist model, it is employed in deepImageJ to create the masks, followed by StarDist postprocessing. The pipeline is completed with the application of Connected Components for 3D visualization. All 3D volumes are displayed as Z-projections.