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Determination of Image-based Biomarkers for the Diagnosis of Hypertrophic Cardiomyopathy, Hypertensive Cardiomyopathy and Amyloidosis From Texture Analysis in Cardiac MRI

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Determination of Image-based Biomarkers for the Diagnosis of Hypertrophic Cardiomyopathy, Hypertensive Cardiomyopathy and Amyloidosis From Texture Analysis in Cardiac MRI

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dc.contributor.author Vidal Sospedra, Inés es_ES
dc.contributor.author Ruiz-España, Silvia es_ES
dc.contributor.author Piñeiro-Vidal, Tania es_ES
dc.contributor.author Santabárbara, JM es_ES
dc.contributor.author Maceira, Alicia es_ES
dc.contributor.author Moratal, David es_ES
dc.date.accessioned 2022-01-18T08:12:19Z
dc.date.available 2022-01-18T08:12:19Z
dc.date.issued 2020-10-28 es_ES
dc.identifier.isbn 978-1-7281-9574-2 es_ES
dc.identifier.issn 2471-7819 es_ES
dc.identifier.uri http://hdl.handle.net/10251/179814
dc.description.abstract [EN] Hypertrophic cardiomyopathy (HCM), hypertensive cardiomyopathy (HIP), and amyloidosis (AM) are pathologies in which a thickening of a portion of the myocardium occurs. All of them are manifested in a similar way on magnetic resonance images, which means that in most cases it is necessary to resort to the use of invasive diagnostic techniques. The objective of this work is to develop quantitative biomarkers that can differentiate between patients with these three pathologies using texture analysis on cardiac magnetic resonance imaging (MRI). In this study, a total of 103 patients underwent cine MRI. Two studies were carried out, one binary with patients with HCM and HIP and one multiclass considering the three pathologies. The left ventricular myocardium was segmented according to the standardized 17-segment model. A total of 43 features for each of the six segments were extracted using 5 different statistical methods. Four predictive models were implemented to evaluate the performance of the classification. Good precision results were obtained in both studies. For the binary study, a maximum AUC of 0.91 +/- 0.06 was obtained with the K-Nearest Neighbours model and for the multiclass study the best performance (AUC = 0.89 +/- 0.12) was achieved using the Support Vector Machine classifier. es_ES
dc.description.sponsorship DM acknowledges financial support from the Conselleria d'Educació, Investigació, Cultura i Esport, Generalitat Valenciana (grants AEST/2019/037 and AEST/2020/029), from the Agencia Valenciana de la Innovación, Generalitat Valenciana (ref. INNCAD00/19/085), and from the Centro para el Desarrollo Tecnológico Industrial (Programa Eurostars-2, actuación Interempresas Internacional), Spanish Ministerio de Ciencia, Innovación y Universidades (ref. CIIP20192020). es_ES
dc.language Inglés es_ES
dc.publisher IEEE Computer Society es_ES
dc.relation.ispartof Proceedings. IEEE 20th International Conference on Bioinformatics and Bioengineering. BIBE 2020 es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Hypertrophic cardiomyopathy es_ES
dc.subject Hypertensive cardiomyopathy es_ES
dc.subject Amyloidosis es_ES
dc.subject Magnetic resonance imaging es_ES
dc.subject Heart es_ES
dc.subject Texture analysis es_ES
dc.subject Classification es_ES
dc.subject.classification TECNOLOGIA ELECTRONICA es_ES
dc.title Determination of Image-based Biomarkers for the Diagnosis of Hypertrophic Cardiomyopathy, Hypertensive Cardiomyopathy and Amyloidosis From Texture Analysis in Cardiac MRI es_ES
dc.type Comunicación en congreso es_ES
dc.type Artículo es_ES
dc.type Capítulo de libro es_ES
dc.identifier.doi 10.1109/BIBE50027.2020.00045 es_ES
dc.relation.projectID info:eu-repo/grantAgreement///AEST%2F2019%2F037//AYUDA ESTANCIA EN EMPRESA EXPLORACIONES RADIOLOGICAS ESPECIALES S.L. "CARACTERIZACION DE LA CARDIOMIOPATIA HIPERTROFICA Y DEL CORAZON DE ATLETA"/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement///AEST%2F2020%2F029//Aplicación de técnicas de deep learning (aprendizaje profundo) para un análisis automático de imágenes de Resonancia Magnética cardiaca/ es_ES
dc.rights.accessRights Cerrado es_ES
dc.contributor.affiliation Universitat Politècnica de València. Centro de Biomateriales e Ingeniería Tisular - Centre de Biomaterials i Enginyeria Tissular es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Electrónica - Departament d'Enginyeria Electrònica es_ES
dc.description.bibliographicCitation Vidal Sospedra, I.; Ruiz-España, S.; Piñeiro-Vidal, T.; Santabárbara, J.; Maceira, A.; Moratal, D. (2020). Determination of Image-based Biomarkers for the Diagnosis of Hypertrophic Cardiomyopathy, Hypertensive Cardiomyopathy and Amyloidosis From Texture Analysis in Cardiac MRI. IEEE Computer Society. 230-235. https://doi.org/10.1109/BIBE50027.2020.00045 es_ES
dc.description.accrualMethod S es_ES
dc.relation.conferencename IEEE 20th International Conference on BioInformatics and BioEngineering (BIBE 2020) es_ES
dc.relation.conferencedate Octubre 26-28,2020 es_ES
dc.relation.conferenceplace Online es_ES
dc.relation.publisherversion https://doi.org/10.1109/BIBE50027.2020.00045 es_ES
dc.description.upvformatpinicio 230 es_ES
dc.description.upvformatpfin 235 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.relation.pasarela S\428031 es_ES


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