{"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/segmenting-root-systems-in-x-ray-computed","title":"Segmenting root systems in X-ray computed tomography images using level sets","arxiv_id":"1809.06398","date":"2018-09-17","proceeding":null,"authors":["Amy Tabb","Keith E. Duncan","Christopher N. Topp"],"abstract":"The segmentation of plant roots from soil and other growing media in X-ray\ncomputed tomography images is needed to effectively study the root system\narchitecture without excavation. However, segmentation is a challenging problem\nin this context because the root and non-root regions share similar features.\nIn this paper, we describe a method based on level sets and specifically\nadapted for this segmentation problem. In particular, we deal with the issues\nof using a level sets approach on large image volumes for root segmentation,\nand track active regions of the front using an occupancy grid. This method\nallows for straightforward modifications to a narrow-band algorithm such that\nexcessive forward and backward movements of the front can be avoided, distance\nmap computations in a narrow band context can be done in linear time through\nmodification of Meijster et al.'s distance transform algorithm, and regions of\nthe image volume are iteratively used to estimate distributions for root versus\nnon-root classes. Results are shown of three plant species of different\nmaturity levels, grown in three different media. Our method compares favorably\nto a state-of-the-art method for root segmentation in X-ray CT image volumes.","url_abs":"http://arxiv.org/abs/1809.06398v1","url_pdf":"http://arxiv.org/pdf/1809.06398v1.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":"segmenting-root-systems-in-x-ray-computed","repo_url":"https://github.com/amy-tabb/tabb-level-set-segmentation","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"segmentation","task_name":"Segmentation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}