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
Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/179814
Título:
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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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Autor:
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Vidal Sospedra, Inés
Ruiz-España, Silvia
Piñeiro-Vidal, Tania
Santabárbara, JM
Maceira, Alicia
Moratal, David
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Entidad UPV:
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Universitat Politècnica de València. Centro de Biomateriales e Ingeniería Tisular - Centre de Biomaterials i Enginyeria Tissular
Universitat Politècnica de València. Departamento de Ingeniería Electrónica - Departament d'Enginyeria Electrònica
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Fecha difusión:
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Resumen:
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[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 ...[+]
[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.
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Palabras clave:
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Hypertrophic cardiomyopathy
,
Hypertensive cardiomyopathy
,
Amyloidosis
,
Magnetic resonance imaging
,
Heart
,
Texture analysis
,
Classification
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Derechos de uso:
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Cerrado |
ISBN:
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978-1-7281-9574-2
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Fuente:
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Proceedings. IEEE 20th International Conference on Bioinformatics and Bioengineering. BIBE 2020. (issn:
2471-7819
)
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DOI:
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10.1109/BIBE50027.2020.00045
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Editorial:
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IEEE Computer Society
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Versión del editor:
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https://doi.org/10.1109/BIBE50027.2020.00045
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Título del congreso:
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IEEE 20th International Conference on BioInformatics and BioEngineering (BIBE 2020)
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Lugar del congreso:
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Online
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Fecha congreso:
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Octubre 26-28,2020
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Código del Proyecto:
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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"/
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/
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Agradecimientos:
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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, Generalita ...[+]
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).
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Tipo:
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Comunicación en congreso
Artículo
Capítulo de libro
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