128005 20231027135453.0 doi 10.38207/jmcrcs20201042 sideral 120375 ART-2020-120375 eng Ávila Gómez, Francisco Javier Universidad de Zaragoza (orcid)0000-0002-9068-7728 Superpixel Segmentation of Chest Computerized Tomographic Images from COVID-19 Disease Patients 2020 Coronavirus disease (COVID-19) is an infectious disease caused by the SARS-CoV-2 virus that has caused a global pandemic with hundreds of thousands of deaths worldwide. The severity of the disease and the lack of an effective treatment or vaccine have promoted hundreds of simultaneous scientific research throughout the world searching in parallel a cure and accurate diagnostic methods. This work presents a userfriendly and fast novel method based on superpixel segmentation to analyze chest CT images to detect and study positive COVID-19 cases. Access copy available to the general public Unrestricted info:eu-repo/semantics/openAccess by http://creativecommons.org/licenses/by/3.0/es/ info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Embid, Ismael Marcellán, Mª Concepción Universidad de Zaragoza (orcid)0000-0002-7516-3029 Remón, Laura Universidad de Zaragoza (orcid)0000-0002-3979-4528 2002 647 Universidad de Zaragoza Dpto. Física Aplicada Área Óptica 1, 3 (2020), [5 pp.] J. med. case rep. case ser. Journal of medical case reports and case series 2692-9880 779349 http://zaguan.unizar.es/record/128005/files/texto_completo.pdf Versión publicada 4218678 http://zaguan.unizar.es/record/128005/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:128005 articulos driver 2023-10-27-11:22:50 ARTICLE