Filtering of the skin portion on lung ultrasound digital images to facilitate automatic diagnostics of pneumonia

dc.contributor.affiliationPontificia Universidad Católica del Perú. Departamento de Ingeniería
dc.contributor.authorBarrientos-Porras, F.
dc.contributor.authorRoman-Gonzalez, A.
dc.contributor.authorBarrientos, R.
dc.contributor.authorSolis-Vasquez, L.
dc.contributor.authorAlva-Mantari, A.
dc.contributor.authorCorrea, M.
dc.contributor.authorPajuelo, M.
dc.contributor.authorAnticona, C.
dc.contributor.authorLavarello Montero, R.
dc.contributor.authorCastañeda, B.
dc.contributor.authorOberhelman, R.
dc.contributor.authorGilman, R.H.
dc.contributor.authorZimic, M.
dc.date.accessioned2026-03-13T16:58:49Z
dc.date.issued2016
dc.description.abstractPneumonia is one of the major causes of child mortality, but it is curable if one can achieves early diagnostics. Unfortunately, in developing countries there is a lack of infrastructure and medical experts in rural areas to provide the required diagnostics opportunely. Lung ultrasound echography has proved to be an important tool to detect lung consolidates as evidence of pneumonia. The use of ultrasound to detect pneumonia is limited by the image analysis for interpretation, which is carried by human experts. Pattern recognition and image analysis is a potential tool to facilitate recognition of pneumonia consolidates in absence of medical experts for automatic diagnostics. To perform an automatic analysis of lung ultrasound images for pneumonia detection, the noise introduced by the image portion of the skin, notably complicates the processing and interpretation. This paper presents a methodology to recognize and eliminate the portion of the skin in lung ultrasound images.
dc.description.sponsorshipFunding: This work was supported by NIH-1D43TW009349-03, Grand Challenge Canada 0542-01-10, Grand Challenge Canada 0688-01-10, CONCYTEC-FONDECYT 054-2014, PUCP-DGI 70242-2149, and 1-2013-Fondecyt.
dc.identifier.doihttps://doi.org/10.1109/CONCAPAN.2016.7942376
dc.identifier.urihttp://hdl.handle.net/20.500.14657/206051
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers
dc.relation.conferencename2016 IEEE 36th Central American and Panama Conventión, CONCAPAN 2016 (2016)
dc.relation.ispartofurn:isbn:9781467395786
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectPneumonia
dc.subjectUltrasound
dc.subjectComputer science
dc.subjectLung ultrasound
dc.subjectMedical imaging
dc.subjectComputer vision
dc.subjectArtificial intelligence
dc.subjectImage processing
dc.subjectLung
dc.subjectRadiology
dc.subjectMedicine
dc.subjectImage (mathematics)
dc.subject.ocdehttps://purl.org/pe-repo/ocde/ford#3.02.02
dc.titleFiltering of the skin portion on lung ultrasound digital images to facilitate automatic diagnostics of pneumonia
dc.typehttp://purl.org/coar/resource_type/c_5794
dc.type.otherComunicación de congreso
dc.type.versionhttps://vocabularies.coar-repositories.org/version_types/c_970fb48d4fbd8a85/

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