ArticleBMC bioinformatics2021
PartSeg: a tool for quantitative feature extraction from 3D microscopy images for dummies.
Article in BMC bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Transcriptional activity during seed imbibition is conserved, robust and required for germination.Nature communications · 2026Article
- UBA2A regulates seed dormancy and the stability of chromatin-retained DOG1 messenger RNA.Journal of integrative plant biology · 2025Article
- Cecelia: a multifunctional image analysis toolbox for decoding spatial cellular interactions and behaviour.Nature communications · 2025Article
- Dormancy heterogeneity among Arabidopsis thaliana seeds is linked to individual seed size.Plant communications · 2024Article
- A multiparametric analysis including single-cell and subcellular feature assessment reveals differential behavior of spheroid cultures on distinct ultra-low attachment plate types.Frontiers in bioengineering and biotechnology · 2024Article
- Secretomes of M1 and M2 macrophages decrease the release of neutrophil extracellular traps.Scientific reports · 2023Article
- Promoter-pervasive transcription causes RNA polymerase II pausing to boost DOG1 expression in response to salt.The EMBO journal · 2023Article
- Trapalyzer: a computer program for quantitative analyses in fluorescent live-imaging studies of neutrophil extracellular trap formation.Frontiers in immunology · 2023Article
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9 authors.
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Abstract
backgroundBioimaging techniques offer a robust tool for studying molecular pathways and morphological phenotypes of cell populations subjected to various conditions. As modern high-resolution 3D microscopy provides access to an ever-increasing amount of high-quality images, there arises a need for their analysis in an automated, unbiased, and simple way. Segmentation of structures within the cell nucleus, which is the focus of this paper, presents a new layer of complexity in the form of dense packing and significant signal overlap. At the same time, the available segmentation tools provide a steep learning curve for new users with a limited technical background. This is especially apparent in the bulk processing of image sets, which requires the use of some form of programming notation.
resultsIn this paper, we present PartSeg, a tool for segmentation and reconstruction of 3D microscopy images, optimised for the study of the cell nucleus. PartSeg integrates refined versions of several state-of-the-art algorithms, including a new multi-scale approach for segmentation and quantitative analysis of 3D microscopy images. The features and user-friendly interface of PartSeg were carefully planned with biologists in mind, based on analysis of multiple use cases and difficulties encountered with other tools, to offer an ergonomic interface with a minimal entry barrier. Bulk processing in an ad-hoc manner is possible without the need for programmer support. As the size of datasets of interest grows, such bulk processing solutions become essential for proper statistical analysis of results. Advanced users can use PartSeg components as a library within Python data processing and visualisation pipelines, for example within Jupyter notebooks. The tool is extensible so that new functionality and algorithms can be added by the use of plugins. For biologists, the utility of PartSeg is presented in several scenarios, showing the quantitative analysis of nuclear structures.
conclusionsIn this paper, we have presented PartSeg which is a tool for precise and verifiable segmentation and reconstruction of 3D microscopy images. PartSeg is optimised for cell nucleus analysis and offers multi-scale segmentation algorithms best-suited for this task. PartSeg can also be used for the bulk processing of multiple images and its components can be reused in other systems or computational experiments.
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