{"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/lgan-lung-segmentation-in-ct-scans-using","title":"LGAN: Lung Segmentation in CT Scans Using Generative Adversarial Network","arxiv_id":"1901.03473","date":"2019-01-11","proceeding":null,"authors":["Jiaxing Tan","Longlong Jing","Yumei Huo","YingLi Tian","Oguz Akin"],"abstract":"Lung segmentation in computerized tomography (CT) images is an important\nprocedure in various lung disease diagnosis. Most of the current lung\nsegmentation approaches are performed through a series of procedures with\nmanually empirical parameter adjustments in each step. Pursuing an automatic\nsegmentation method with fewer steps, in this paper, we propose a novel deep\nlearning Generative Adversarial Network (GAN) based lung segmentation schema,\nwhich we denote as LGAN. Our proposed schema can be generalized to different\nkinds of neural networks for lung segmentation in CT images and is evaluated on\na dataset containing 220 individual CT scans with two metrics: segmentation\nquality and shape similarity. Also, we compared our work with current state of\nthe art methods. The results obtained with this study demonstrate that the\nproposed LGAN schema can be used as a promising tool for automatic lung\nsegmentation due to its simplified procedure as well as its good performance.","url_abs":"http://arxiv.org/abs/1901.03473v1","url_pdf":"http://arxiv.org/pdf/1901.03473v1.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":"lgan-lung-segmentation-in-ct-scans-using","repo_url":"https://github.com/DavidSriker/LGAN","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":null,"task_name":"Generative Adversarial Network"},{"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}