Please use this identifier to cite or link to this item: http://ricaxcan.uaz.edu.mx/jspui/handle/20.500.11845/1619
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dc.contributor429892es_ES
dc.contributor.otherhttps://orcid.org/0000-0002-7635-4687-
dc.contributor.otherhttps://orcid.org/0000-0001-6082-1546-
dc.coverage.spatialGlobales_ES
dc.creatorGalván Tejada, Jorge Issac-
dc.creatorGalván Tejada, Carlos Eric-
dc.creatorLópez Monteagudo, Francisco Eneldo-
dc.creatorAlonso González, Omero-
dc.creatorMoreno Báez, Arturo-
dc.creatorCelaya Padilla, José María-
dc.creatorZanella Calzada, Laura Alejandra-
dc.date.accessioned2020-04-14T17:38:47Z-
dc.date.available2020-04-14T17:38:47Z-
dc.date.issued2019-01-24-
dc.identifierinfo:eu-repo/semantics/publishedVersiones_ES
dc.identifier.issn2395-9126es_ES
dc.identifier.urihttp://ricaxcan.uaz.edu.mx/jspui/handle/20.500.11845/1619-
dc.identifier.urihttps://doi.org/10.48779/yp30-xm13-
dc.descriptionOsteoarthritis (OA) is the most common type of arthritis, is a growing disease in the industrialized world. OA is an incapacitate disease that affects more than 1 in 10 adults over 60 years old. X-ray medical imaging is a primary diagnose technique used on staging OA that the expert reads and quantify the stage of the disease. Some Computer-Aided Diagnosis (CADx) efforts to automate the OA detection have been made to aid the radiologist in the detection and control, nevertheless, the pain inherits to the disease progression is left behind. In this research, it’s proposed a CADx system that quantify the bilateral similarity of the patient’s knees to correlate the degree of asymmetry with the pain development. Firstly, the knee images were aligned using a B-spline image registration algorithm, then, a set of similarity measures were quantified, lastly, using this measures it’s proposed a multivariate model to predict the pain development up to 48 months. The methodology was validated on a cohort of 131 patients from the Osteoarthritis Initiative (OAI) database. Results suggest that mutual information can be associated with K&L OAI scores, and Multivariate models predicted knee chronic pain with: AUC 0.756, 0.704, 0.713 at baseline, one year, and two years’ follow-up.es_ES
dc.description.abstractOsteoarthritis (OA) is the most common type of arthritis, is a growing disease in the industrialized world. OA is an incapacitate disease that affects more than 1 in 10 adults over 60 years old. X-ray medical imaging is a primary diagnose technique used on staging OA that the expert reads and quantify the stage of the disease. Some Computer-Aided Diagnosis (CADx) efforts to automate the OA detection have been made to aid the radiologist in the detection and control, nevertheless, the pain inherits to the disease progression is left behind. In this research, it’s proposed a CADx system that quantify the bilateral similarity of the patient’s knees to correlate the degree of asymmetry with the pain development. Firstly, the knee images were aligned using a B-spline image registration algorithm, then, a set of similarity measures were quantified, lastly, using this measures it’s proposed a multivariate model to predict the pain development up to 48 months. The methodology was validated on a cohort of 131 patients from the Osteoarthritis Initiative (OAI) database. Results suggest that mutual information can be associated with K&L OAI scores, and Multivariate models predicted knee chronic pain with: AUC 0.756, 0.704, 0.713 at baseline, one year, and two years’ follow-up.es_ES
dc.language.isoenges_ES
dc.publisherSociedad Mexicana de Ingeniería Biomédica A.C.es_ES
dc.relation.urigeneralPublices_ES
dc.rightsAtribución-NoComercial-CompartirIgual 3.0 Estados Unidos de América*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/us/*
dc.sourceRevista Mexicana de Ingeniería Biomédica, Vol. 40, No 1, enero-abril 2019,es_ES
dc.subject.classificationINGENIERIA Y TECNOLOGIA [7]es_ES
dc.subject.otherOsteoarthritis Initiativees_ES
dc.subject.otherbiomarkeres_ES
dc.subject.otherKellgrenLawrence gradees_ES
dc.subject.otherknee registrationes_ES
dc.subject.otherpain predictiones_ES
dc.titleImage Registration Measures and Chronic Osteoarthritis Knee Pain Prediction: Data from the Osteoarthritis Initiativees_ES
dc.title.alternativeMétricas de Registro de Imágenes y Predicción de Dolor de Rodilla por Osteoartritis Crónica: Datos de la Osteoarthritis Initiativees_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
Appears in Collections:*Documentos Académicos*-- M. en Ciencias de la Ing.

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