{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/fast-determination-of-coarse-grained-cell","title":"Fast determination of coarse grained cell anisotropy and size in epithelial tissue images using Fourier transform","arxiv_id":"1810.11652","date":"2019-03-17","proceeding":null,"authors":[],"abstract":"Mechanical strain and stress play a major role in biological processes such\nas wound healing or morphogenesis. To assess this role quantitatively, fixed or\nlive images of tissues are acquired at a cellular precision in large fields of\nviews. To exploit these data, large numbers of cells have to be analyzed to\nextract cell shape anisotropy and cell size. Most frequently, this is performed\nthrough detailed individual cell contour determination, using so-called\nsegmentation computer programs, complemented if necessary by manual detection\nand error corrections. However, a coarse grained and faster technique can be\nrecommended in at least three situations. First, when detailed information on\nindividual cell contours is not required, for instance in studies which require\nonly coarse-grained average information on cell anisotropy. Second, as an\nexploratory step to determine whether full segmentation can be potentially\nuseful. Third, when segmentation is too difficult, for instance due to poor\nimage quality or too large a cell number. We developed a user-friendly, Fourier\ntransform-based image analysis pipeline. It is fast (typically $10^4$ cells per\nminute with a current laptop computer) and suitable for time, space or ensemble\naverages. We validate it on one set of artificial images and on two sets of\nfully segmented images, one from a Drosophila pupa and the other from a chicken\nembryo; the pipeline results are robust. Perspectives include \\textit{in vitro}\ntissues, non-biological cellular patterns such as foams, and $xyz$ stacks.","url_abs":"http://arxiv.org/abs/1810.11652v3","url_pdf":"http://arxiv.org/pdf/1810.11652v3.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"fast-determination-of-coarse-grained-cell","repo_url":"https://github.com/mdurande/coarse-grained-anisotropy-and-size-using-FFT","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"segmentation","task_name":"Segmentation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}