dc.creatorContreras Ojeda, Sara
dc.creatorSierra-Pardo C.
dc.creatorDomínguez Jiménez, Juan Antonio
dc.creatorLópez-Bueno J.
dc.creatorContreras Ortiz, Sonia Helena
dc.date.accessioned2020-03-26T16:33:04Z
dc.date.available2020-03-26T16:33:04Z
dc.date.created2020-03-26T16:33:04Z
dc.date.issued2019
dc.identifier2019 22nd Symposium on Image, Signal Processing and Artificial Vision, STSIVA 2019 - Conference Proceedings
dc.identifier9781728114910
dc.identifierhttps://hdl.handle.net/20.500.12585/9153
dc.identifier10.1109/STSIVA.2019.8730238
dc.identifierUniversidad Tecnológica de Bolívar
dc.identifierRepositorio UTB
dc.identifier57209529596
dc.identifier57209540733
dc.identifier56682770100
dc.identifier57209534730
dc.identifier57210822856
dc.description.abstractPneumonia is a condition that can be life-threatening and affects a high number of children around the world. Lung ultrasound can be used for the diagnosis of pneumonia, but requires high experience. This paper presents an approach for pneumonia detection based on texture analysis of ultrasound images. Several measures were taken in healthy tissues and pneumonia lesions, and the most significant features were identified by statistical analysis. The results of the analysis of variance and exploratory analysis suggest that detection of pneumonia is possible based on image texture features. © 2019 IEEE.
dc.languageeng
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation24 April 2019 through 26 April 2019
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.rightsAtribución-NoComercial 4.0 Internacional
dc.sourcehttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85068092598&doi=10.1109%2fSTSIVA.2019.8730238&partnerID=40&md5=8e6e8606e1550f0ed1795969ede9b409
dc.sourceScopus2-s2.0-85068092598
dc.source22nd Symposium on Image, Signal Processing and Artificial Vision, STSIVA 2019
dc.titleTexture Analysis of Ultrasound Images for Pneumonia Detection in Pediatric Patients


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