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Combining machine learning and close-range photogrammetry for infant's head 3D measurement: A smartphone-based solution

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Combining machine learning and close-range photogrammetry for infant's head 3D measurement: A smartphone-based solution

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dc.contributor.author Barbero-García, Inés es_ES
dc.contributor.author Pierdicca, Roberto es_ES
dc.contributor.author Paolanti, Marina es_ES
dc.contributor.author Felicetti, Andrea es_ES
dc.contributor.author Lerma, José Luis es_ES
dc.date.accessioned 2023-11-03T19:01:52Z
dc.date.available 2023-11-03T19:01:52Z
dc.date.issued 2021-09 es_ES
dc.identifier.issn 0263-2241 es_ES
dc.identifier.uri http://hdl.handle.net/10251/199209
dc.description.abstract [EN] Three-dimensional data has a wide range of applications in medicine. For the particular case of cranial deformation in infants, it is becoming a common tool for evaluation. However, there is a need for low-cost solutions that provide accurate information even with uncoll aborative infants with ultrafast movement reactions. As cranial deformation is often linked to facial abnormalities, facial information is required for comprehensive evaluation. In this study, the integration of target-based close-range photogrammetry and facial landmark machine learning detection is carried out. The resulting tool is automatic and smartphone-based and provides 3D information of the head and face. This methodology opens a new path for the effective integration of machine learning and photogrammetry in medicine and, in particular, for overall head analysis. es_ES
dc.description.sponsorship This work was supported by the Instituto de Salud Carlos III and European Regional Development Fund (FEDER) , project number PI18/00881. es_ES
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation.ispartof Measurement es_ES
dc.rights Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) es_ES
dc.subject 3D data acquisition es_ES
dc.subject Smartphone es_ES
dc.subject Facial landmark detection es_ES
dc.subject Plagiocephaly es_ES
dc.subject Photogrammetry es_ES
dc.subject.classification INGENIERIA CARTOGRAFICA, GEODESIA Y FOTOGRAMETRIA es_ES
dc.title Combining machine learning and close-range photogrammetry for infant's head 3D measurement: A smartphone-based solution es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.measurement.2021.109686 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/INSTITUTO DE SALUD CARLOS III//PI18%2F00881//ANALISIS Y MONITORIZACION NO INVASIVA Y DE BAJO COSTE DE LA DEFORMACION CRANEAL EN LACTANTES MEDIANTE FOTOGRAMETRIA 3D Y TELEFONOS INTELIGENTES/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escuela Técnica Superior de Ingeniería Geodésica, Cartográfica y Topográfica - Escola Tècnica Superior d'Enginyeria Geodèsica, Cartogràfica i Topogràfica es_ES
dc.description.bibliographicCitation Barbero-García, I.; Pierdicca, R.; Paolanti, M.; Felicetti, A.; Lerma, JL. (2021). Combining machine learning and close-range photogrammetry for infant's head 3D measurement: A smartphone-based solution. Measurement. 182:1-10. https://doi.org/10.1016/j.measurement.2021.109686 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1016/j.measurement.2021.109686 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 10 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 182 es_ES
dc.relation.pasarela S\488645 es_ES
dc.contributor.funder INSTITUTO DE SALUD CARLOS III es_ES
dc.contributor.funder European Regional Development Fund es_ES


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