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Region of interest-bounded COVID-19 lung screening using images from portable X-ray devices
dc.contributor.author | Vidal, Plácido | |
dc.contributor.author | Moura, Joaquim de | |
dc.contributor.author | Ramos, Lucía | |
dc.contributor.author | Novo Buján, Jorge | |
dc.contributor.author | Ortega Hortas, Marcos | |
dc.date.accessioned | 2024-06-03T17:40:30Z | |
dc.date.available | 2024-06-03T17:40:30Z | |
dc.date.issued | 2023 | |
dc.identifier.citation | Vidal, P. L., de Moura, J., Ramos, L., Novo, J., & Ortega, M. (2023). Region of interest-bounded COVID-19 lung screening using images from portable X-ray devices. In Proceedings of V XoveTIC Conference. XoveTIC (Vol. 14, pp. 111-114). https://doi.org/10.29007/cj6l | es_ES |
dc.identifier.issn | 2515-1762 | |
dc.identifier.uri | http://hdl.handle.net/2183/36788 | |
dc.description | Comunicación presentada al V Congreso XoveTIC, organizado por el Centro de Investigación en TIC da Universidade da Coruña (CITIC), os días 5 y 6 de octubre de 2022 | es_ES |
dc.description.abstract | [Abstract]: X-ray analysis of the lungs was the main method to assess the degree of affliction of SARS-COV-2. Due to the high contagiousness of this pathology, this assessment was conducted using portable X-ray devices. Automatic methodologies were proposed to compensate the image quality of said portable X-ray devices. However, these methodologies were shown to be exploiting external information (such as pacemakers or ventilators present in the images) to determine the severity. For this reason, we present a methodology specially designed to reduce the effect on an automatic methodology of these extraneous artifacts. We extract the lung region and we perform a screening of the presence of the pathology using only the pulmonary region. Finally, to ascertain the performance of the system (and provide explainability to the clinical experts), we generate the corresponding activation maps. The presented methodology has achieved a more than satisfactory performance in all the scenarios and the activation maps clearly indicate that the system is successfully using information from the lung region while excluding elements unrelated to the disease. | es_ES |
dc.description.sponsorship | This research was funded by: Instituto de Salud Carlos III - DTS18/00136; Ministerio de Ciencia e Innovación y Universidades, Gov. of Spain - RTI2018-095894-B-I00, Ayudas para la formación de prof. universitario (FPU)- FPU18/02271; Ministerio de Ciencia e Innovación, Gov. of Spain - PID2019-108435RB-I00; Conselleria de Cultura, Educación e Universidade, Xunta de Galicia, Grupos de Referencia Competitiva - ED431C 2020/24; Axencia Galega de Innovación (GAIN), Xunta de Galicia - IN845D 2020/38; CITIC, Centro de Investigación de Galicia ref. ED431G 2019/01, receives financial support from Consellería de Educación, Universidade e Formación Profesional, Xunta de Galicia, through the ERDF (80%) and Secretaría Xeral de Universidades (20%). | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED431C 2020/24 | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED431G 2019/01 | es_ES |
dc.description.sponsorship | Xunta de Galicia; IN845D 2020/38 | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | EasyChair | es_ES |
dc.relation | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-108435RB-I00/ES/CUANTIFICACION Y CARACTERIZACION COMPUTACIONAL DE IMAGEN MULTIMODAL OFTALMOLOGICA: ESTUDIOS EN ESCLEROSIS MULTIPLE | es_ES |
dc.relation | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-095894-B-I00/ES/DESARROLLO DE TECNOLOGIAS INTELIGENTES PARA DIAGNOSTICO DE LA DMAE BASADAS EN EL ANALISIS AUTOMATICO DE NUEVAS MODALIDADES HETEROGENEAS DE ADQUISICION DE IMAGEN OFTALMOLOGICA | es_ES |
dc.relation | info:eu-repo/grantAgreement/MICINN/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/DTS18%2F00136/ES/Plataforma online para prevención y detección precoz de enfermedad vascular mediante análisis automatizado de información e imagen clínica | es_ES |
dc.relation | info:eu-repo/grantAgreement/MECD/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/FPU18%2F02271/ES/ | es_ES |
dc.relation.uri | https://doi.org/10.29007/cj6l | es_ES |
dc.subject | CAD system | es_ES |
dc.subject | COVID-19 | es_ES |
dc.subject | Lung segmentation | es_ES |
dc.subject | Radiography | es_ES |
dc.subject | Screening | es_ES |
dc.subject | X-ray | es_ES |
dc.title | Region of interest-bounded COVID-19 lung screening using images from portable X-ray devices | es_ES |
dc.type | info:eu-repo/semantics/conferenceObject | es_ES |
dc.type | info:eu-repo/semantics/conferenceObject | es_ES |
dc.rights.access | info:eu-repo/semantics/openAccess | es_ES |
UDC.journalTitle | Kalpa Publications in Computing | es_ES |
UDC.volume | 14 | es_ES |
UDC.startPage | 111 | es_ES |
UDC.endPage | 114 | es_ES |
dc.identifier.doi | 10.29007/cj6l | |
UDC.conferenceTitle | V XoveTIC Conference. XoveTIC 2022 | es_ES |