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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\u00a0cell 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\u00a0limited technical background. This is especially apparent in the\u00a0bulk processing of image sets, which requires the use of some form of programming notation.<\/jats:p>\n <\/jats:sec>\n Results<\/jats:title>\n In this paper, we present PartSeg, a tool for segmentation and reconstruction of 3D microscopy images, optimised for the study of\u00a0the 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\u00a0ergonomic 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.<\/jats:p>\n <\/jats:sec>\n Conclusions<\/jats:title>\n In 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\u00a0bulk processing of multiple images and its components can be reused in other systems or computational experiments.<\/jats:p>\n <\/jats:sec>","DOI":"10.1186\/s12859-021-03984-1","type":"journal-article","created":{"date-parts":[[2021,2,18]],"date-time":"2021-02-18T08:00:13Z","timestamp":1613635213000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["PartSeg: a tool for quantitative feature extraction from 3D microscopy images for dummies"],"prefix":"10.1186","volume":"22","author":[{"given":"Grzegorz","family":"Bokota","sequence":"first","affiliation":[]},{"given":"Jacek","family":"Sroka","sequence":"additional","affiliation":[]},{"given":"Subhadip","family":"Basu","sequence":"additional","affiliation":[]},{"given":"Nirmal","family":"Das","sequence":"additional","affiliation":[]},{"given":"Pawel","family":"Trzaskoma","sequence":"additional","affiliation":[]},{"given":"Yana","family":"Yushkevich","sequence":"additional","affiliation":[]},{"given":"Agnieszka","family":"Grabowska","sequence":"additional","affiliation":[]},{"given":"Adriana","family":"Magalska","sequence":"additional","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0000-0002-3840-7610","authenticated-orcid":false,"given":"Dariusz","family":"Plewczynski","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,2,17]]},"reference":[{"key":"3984_CR1","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1016\/j.micron.2014.01.009","volume":"61","author":"CJ Peddie","year":"2014","unstructured":"Peddie CJ, Collinson LM. 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