Efficient use of mobile devices for quantification of pressure injury images

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dc.contributor.authorGarcia-Zapirain B
dc.contributor.authorSierra-Sosa D
dc.contributor.authorOrtiz P D
dc.contributor.authorIsaza-Monsalve M
dc.contributor.authorElmaghraby A
dc.contributor.departmentUniversidad EAFIT. Departamento de Cienciasspa
dc.contributor.researchgroupModelado Matemáticospa
dc.creatorGarcia-Zapirain B
dc.creatorSierra-Sosa D
dc.creatorOrtiz P D
dc.creatorIsaza-Monsalve M
dc.creatorElmaghraby A
dc.date.accessioned2021-04-12T14:11:49Z
dc.date.available2021-04-12T14:11:49Z
dc.date.issued2018-01-01
dc.description.abstractPressure Injuries are chronic wounds that are formed due to the constriction of the soft tissues against bone prominences. In order to assess these injuries, the medical personnel carry out the evaluation and diagnosis using visual methods and manual measurements, which can be inaccurate and may generate discomfort in the patients. By using segmentation techniques, the Pressure Injuries can be extracted from an image and accurately parameterized, leading to a correct diagnosis. In general, these techniques are based on the solution of differential equations and the involved numerical methods are demanding in terms of computational resources. In previous work, we proposed a technique developed using toroidal parametric equations for image decomposition and segmentation without solving differential equations. In this paper, we present the development of a mobile application useful for the non-contact assessment of Pressure Injuries based on the toroidal decomposition from images. The usage of this technique allows us to achieve an accurate segmentation almost 8 times faster than Active Contours without Edges (ACWE) and Dynamic Contours methods.We describe the techniques and the implementation for Android devices using Python and Kivy. This application allows for the segmentation and parameterization of injuries, obtain relevant information for the diagnosis and tracking the evolution of patient's injuries. © 2018 - IOS Press and the authors.eng
dc.identifierhttps://eafit.fundanetsuite.com/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=8084
dc.identifier.doi10.3233/THC-174612
dc.identifier.issn09287329
dc.identifier.issn18787401
dc.identifier.otherWOS;000433978400026
dc.identifier.otherPUBMED;29710755
dc.identifier.otherSCOPUS;2-s2.0-85049391441
dc.identifier.urihttp://hdl.handle.net/10784/27902
dc.language.isoengeng
dc.publisherIOS Press
dc.relation.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85049391441&doi=10.3233%2fTHC-174612&partnerID=40&md5=3ca01b610388e173dd1cedbe932637d2
dc.rightshttps://v2.sherpa.ac.uk/id/publication/issn/0928-7329
dc.sourceTECHNOLOGY AND HEALTH CARE
dc.subject.keywordartifacteng
dc.subject.keywordchronic woundeng
dc.subject.keywordConference Papereng
dc.subject.keyworddecubituseng
dc.subject.keywordfollow upeng
dc.subject.keywordhumaneng
dc.subject.keywordimage processingeng
dc.subject.keywordimage reconstructioneng
dc.subject.keywordimage segmentationeng
dc.subject.keywordinfectioneng
dc.subject.keywordmobile applicationeng
dc.subject.keywordpriority journaleng
dc.subject.keywordalgorithmeng
dc.subject.keywordchronic diseaseeng
dc.subject.keyworddecubituseng
dc.subject.keyworddiagnostic imagingeng
dc.subject.keywordprocedureseng
dc.subject.keywordsensitivity and specificityeng
dc.subject.keywordAlgorithmseng
dc.subject.keywordChronic Diseaseeng
dc.subject.keywordHumanseng
dc.subject.keywordImage Processing, Computer-Assistedeng
dc.subject.keywordMobile Applicationseng
dc.subject.keywordPressure Ulcereng
dc.subject.keywordSensitivity and Specificityeng
dc.titleEfficient use of mobile devices for quantification of pressure injury imageseng
dc.typeinfo:eu-repo/semantics/conferencePapereng
dc.typeconferencePapereng
dc.typeinfo:eu-repo/semantics/publishedVersioneng
dc.typepublishedVersioneng
dc.type.localDocumento de conferenciaspa

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