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End-systole and end-diastole detection in short axis cine MRI using a fully convolutional neural network with dilated convolutions

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End-systole and end-diastole detection in short axis cine MRI using a fully convolutional neural network with dilated convolutions

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Pérez-Pelegrí, M.; Monmeneu, JV.; López-Lereu, MP.; Maceira, AM.; Bodi, V.; Moratal, D. (2022). End-systole and end-diastole detection in short axis cine MRI using a fully convolutional neural network with dilated convolutions. Computerized Medical Imaging and Graphics. 99:1-8. https://doi.org/10.1016/j.compmedimag.2022.102085

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/197574

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Title: End-systole and end-diastole detection in short axis cine MRI using a fully convolutional neural network with dilated convolutions
Author: Pérez-Pelegrí, Manuel Monmeneu, José V. López-Lereu, María P. Maceira, Alicia M. Bodi, Vicente Moratal, David
UPV Unit: Universitat Politècnica de València. Escuela Técnica Superior de Ingenieros Industriales - Escola Tècnica Superior d'Enginyers Industrials
Issued date:
Abstract:
[EN] The correct assessment and characterization of heart anatomy and functionality is usually done through inspection of magnetic resonance image cine sequences. In the clinical setting it is especially important to ...[+]
Subjects: Cardiac magnetic resonance , Deep learning , Left ventricle , Dilated convolutions , Frame classification
Copyrigths: Reconocimiento - No comercial - Sin obra derivada (by-nc-nd)
Source:
Computerized Medical Imaging and Graphics. (issn: 0895-6111 )
DOI: 10.1016/j.compmedimag.2022.102085
Publisher:
Elsevier
Publisher version: https://doi.org/10.1016/j.compmedimag.2022.102085
Project ID:
info:eu-repo/grantAgreement/GENERALITAT VALENCIANA//AEST%2F2020%2F029//Aplicación de técnicas de deep learning (aprendizaje profundo) para un análisis automático de imágenes de Resonancia Magnética cardiaca/
info:eu-repo/grantAgreement/GENERALITAT VALENCIANA//AEST%2F2021%2F050//ESTABLECIMIENTO DE UN BIOMARCADOR PREDICTOR DEL RIESGO DE.../
Thanks:
Funding sources This work was partially supported by the Conselleria d'Innovació, Universitats, Ciència i Societat Digital, Generalitat Valenciana (grants AEST/2020/029 and AEST/2021/050) .
Type: Artículo

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