Texture analysis in skull magnetic resonance imaging

dc.creatoramelec, viloria
dc.creatorde la Hoz, Ethel
dc.creatorPineda, Omar
dc.date2020-11-12T17:33:59Z
dc.date2020-11-12T17:33:59Z
dc.date2020
dc.date2021-05-07
dc.date.accessioned2023-10-03T19:06:51Z
dc.date.available2023-10-03T19:06:51Z
dc.identifier2194-5357
dc.identifierhttps://hdl.handle.net/11323/7277
dc.identifierCorporación Universidad de la Costa
dc.identifierREDICUC - Repositorio CUC
dc.identifierhttps://repositorio.cuc.edu.co/
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/9167817
dc.descriptionraumatic brain injury (TBI) represents a serious public health problem worldwide. It is the most common cause of death and disability in the young population (aged 15–45 years), with major family, social and economic implications [1]. In medical terms, the human body can be studied as an object. The reconstruction of bone structures after physical damage generated by such an unfortunate event as disease or trauma can range from the implementation of prostheses to the engineering of artificial bone implants [2]. To make a virtual or physical model of any human anatomy, it must first be captured in three dimensions in a way that can be used by computational processes. Most hospital scanners capture data from the entire body both internally and externally. These machines are typically medical imaging devices capable of scanning the entire human body, among which, the most common is the magnetic resonance imaging (MRI) equipment [3]. The goal of the research is to analyze the texture in magnetic resonance imaging and its relationship to bone mineral content (BMC) using simple linear regression.
dc.formatapplication/pdf
dc.formatapplication/pdf
dc.languageeng
dc.publisherCorporación Universidad de la Costa
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dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.rightshttp://purl.org/coar/access_right/c_14cb
dc.sourceAdvances in Intelligent Systems and Computing
dc.sourcehttps://www.scopus.com/record/display.uri?eid=2-s2.0-85089209036&doi=10.1007%2f978-3-030-51859-2_12&origin=inward&txGid=1e875e0c53741f62be937f585a57c8f2
dc.subjectGenetic algorithm
dc.subjectSkull magnetic resonance imaging
dc.subjectTexture analysis
dc.titleTexture analysis in skull magnetic resonance imaging
dc.typePre-Publicación
dc.typehttp://purl.org/coar/resource_type/c_816b
dc.typeText
dc.typeinfo:eu-repo/semantics/preprint
dc.typeinfo:eu-repo/semantics/draft
dc.typehttp://purl.org/redcol/resource_type/ARTOTR
dc.typeinfo:eu-repo/semantics/acceptedVersion
dc.typehttp://purl.org/coar/version/c_ab4af688f83e57aa


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