Classification of normal and abnormal fetal heart ultrasound images and identification of ventricular septal defects based on deep learning.

Yang, Yiru; Wu, Bingzheng; Wu, Huiling; Xu, Wu; Lyu, Guorong; Liu, Peizhong; He, Shaozheng

Yang, Yiru; Wu, Bingzheng; Wu, Huiling; Xu, Wu; Lyu, Guorong; Liu, Peizhong; He, Shaozheng.

Afiliação

Yang Y; The Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian, P.R. China.
Wu B; College of Engineering, Huaqiao University, Quanzhou, Fujian, P.R. China.
Wu H; The Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian, P.R. China.
Xu W; The Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian, P.R. China.
Lyu G; The Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian, P.R. China.
Liu P; Collaborative Innovation Center for Maternal and Infant Health Service Application Technology, Quanzhou Medical College, Quanzhou, Fujian, P.R. China.
He S; College of Engineering, Huaqiao University, Quanzhou, Fujian, P.R. China.

J Perinat Med ; 51(8): 1052-1058, 2023 Oct 26.

Article em En | MEDLINE | ID: mdl-37161929

Assuntos

Aprendizado Profundo; Cardiopatias Congênitas; Comunicação Interventricular; Gravidez; Feminino; Humanos; Inteligência Artificial; Ultrassonografia Pré-Natal/métodos; Comunicação Interventricular/diagnóstico por imagem; Cardiopatias Congênitas/diagnóstico; Coração Fetal/diagnóstico por imagem

Palavras-chave

congenital heart defect; deep learning; prenatal diagnosis

Texto completo

Imprimir

XML

PubMed Links

Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Aprendizado Profundo / Cardiopatias Congênitas / Comunicação Interventricular Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo

Imprimir

XML

PubMed Links

Buscar no Google