- -

PSPU-Net for Automatic Short Axis Cine MRI Segmentation of Left and Right Ventricles

RiuNet: Institutional repository of the Polithecnic University of Valencia

Share/Send to

Cited by

Statistics

  • Estadisticas de Uso

PSPU-Net for Automatic Short Axis Cine MRI Segmentation of Left and Right Ventricles

Show full item record

Pérez-Pelegrí, M.; Monmeneu, JV.; López-Lereu, MP.; Ruiz-España, S.; Del-Canto, I.; Bodi, V.; Moratal, D. (2020). PSPU-Net for Automatic Short Axis Cine MRI Segmentation of Left and Right Ventricles. IEEE Computer Society. 1048-1053. https://doi.org/10.1109/BIBE50027.2020.00177

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/177794

Files in this item

Item Metadata

Title: PSPU-Net for Automatic Short Axis Cine MRI Segmentation of Left and Right Ventricles
Author: Pérez-Pelegrí, Manuel Monmeneu, Jose V. López-Lereu, María P. Ruiz-España, Silvia Del-Canto, Irene Bodi, Vicente Moratal, David
UPV Unit: Universitat Politècnica de València. Departamento de Ingeniería Electrónica - Departament d'Enginyeria Electrònica
Universitat Politècnica de València. Centro de Biomateriales e Ingeniería Tisular - Centre de Biomaterials i Enginyeria Tissular
Issued date:
Abstract:
[EN] Characterization of the heart anatomy and function is mostly done with magnetic resonance image cine series. To achieve a correct characterization, the volume of the right and left ventricle need to be segmented, which ...[+]
Subjects: MRI , U-net , PSP , Segmentation , Deep learning , Left ventricle , Right ventricle , Volume estimation
Copyrigths: Reserva de todos los derechos
ISBN: 978-1-7281-9574-2
Source:
Proceedings. IEEE 20th International Conference on Bioinformatics and Bioengineering. BIBE 2020. (issn: 2471-7819 )
DOI: 10.1109/BIBE50027.2020.00177
Publisher:
IEEE Computer Society
Publisher version: https://doi.org/10.1109/BIBE50027.2020.00177
Conference name: IEEE 20th International Conference on BioInformatics and BioEngineering (BIBE 2020)
Conference place: Online
Conference date: Octubre 26-28,2020
Project ID:
info:eu-repo/grantAgreement/MCIU//CIIP-20192020/
info:eu-repo/grantAgreement/AVI//INNCAD00%2F19%2F085//Proyecto 4DTools: nuevas técnicas y biomarcadores para diagnóstico-pronóstico de patologías de la aorta ascendente a través de técnicas de imagen médica/
info:eu-repo/grantAgreement/GVA//AEST%2F2019%2F037/
info:eu-repo/grantAgreement/GVA//AEST%2F2020%2F029//Aplicación de técnicas de deep learning (aprendizaje profundo) para un análisis automático de imágenes de Resonancia/
Thanks:
DM acknowledges financial support from the Conselleria d'Educacio, Investigacio, Cultura i Esport, Generalitat Valenciana (grants AEST/2019/037 and AEST/2020/029), from the Agencia Valenciana de la Innovacion, Generalitat ...[+]
Type: Comunicación en congreso Artículo Capítulo de libro

recommendations

 

This item appears in the following Collection(s)

Show full item record