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A deep learning system to obtain the optimal parameters for a threshold-based breast and dense tissue segmentation

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A deep learning system to obtain the optimal parameters for a threshold-based breast and dense tissue segmentation

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Perez-Benito, FJ.; Signol, F.; Perez-Cortes, J.; Fuster Bagetto, A.; Pollan, M.; Pérez-Gómez, B.; Salas-Trejo, D.... (2020). A deep learning system to obtain the optimal parameters for a threshold-based breast and dense tissue segmentation. Computer Methods and Programs in Biomedicine. 195:123-132. https://doi.org/10.1016/j.cmpb.2020.105668

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/168615

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Title: A deep learning system to obtain the optimal parameters for a threshold-based breast and dense tissue segmentation
Author: Perez-Benito, Francisco Javier Signol, François Perez-Cortes, Juan-Carlos Fuster Bagetto, Alejandro Pollan, Marina Pérez-Gómez, Beatriz Salas-Trejo, Dolores Casals, Maria Martínez, Inmaculada Llobet Azpitarte, Rafael
UPV Unit: Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació
Universitat Politècnica de València. Departamento de Informática de Sistemas y Computadores - Departament d'Informàtica de Sistemes i Computadors
Issued date:
Abstract:
[EN] Background and Objective: Breast cancer is the most frequent cancer in women. The Spanish healthcare network established population-based screening programs in all Autonomous Communities, where mammograms of asymptomatic ...[+]
Subjects: Breast density , Entirely convolutional neural network (ECNN) , Deep learning , Dense tissue segmentation , Mammography
Copyrigths: Reconocimiento - No comercial - Sin obra derivada (by-nc-nd)
Source:
Computer Methods and Programs in Biomedicine. (issn: 0169-2607 )
DOI: 10.1016/j.cmpb.2020.105668
Publisher:
Elsevier
Publisher version: https://doi.org/10.1016/j.cmpb.2020.105668
Project ID:
info:eu-repo/grantAgreement/IVACE//IMAMCN%2F2019%2F1/ES/Plan de Actividades de carácter no económico 2019/EMOSPACES/
info:eu-repo/grantAgreement/MINECO//DTS15%2F00080/ES/DM-Scan: herramienta de lectura de densidad mamográfica como fenotipo marcador de riesgo de cáncer de mama/
Thanks:
This work was partially funded by Generalitat Valenciana through I+D IVACE (Valencian Institute of Business Competitiviness) and GVA (European Regional Development Fund) supports under the project IMAMCN/2019/1, and by ...[+]
Type: Artículo

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