{"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/seed-point-based-geometric-partitioning-of","title":"Seed-Point Based Geometric Partitioning of Nuclei Clumps","arxiv_id":"1804.04549","date":"2018-04-12","proceeding":null,"authors":["James Kapaldo"],"abstract":"When applying automatic analysis of fluorescence or histopathological images\nof cells, it is necessary to partition, or de-clump, partially overlapping cell\nnuclei. In this work, I describe a method of partitioning partially overlapping\ncell nuclei using a seed-point based geometric partitioning. The geometric\npartitioning creates two different types of cuts, cuts between two boundary\nvertices and cuts between one boundary vertex and a new vertex introduced to\nthe boundary interior. The cuts are then ranked according to a scoring metric,\nand the highest scoring cuts are used. This method was tested on a set of 2420\nclumps of nuclei and was found to produced better results than current popular\nanalysis software.","url_abs":"http://arxiv.org/abs/1804.04549v1","url_pdf":"http://arxiv.org/pdf/1804.04549v1.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":"seed-point-based-geometric-partitioning-of","repo_url":"https://github.com/jkpld/geometricPartitioning","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"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}