Automatic Identification of Bioprostheses on X-ray Angiographic Sequences of Transcatheter Aortic Valve Implantation Procedures Using Deep Learning.

Busto, Laura; Veiga, César; González-Nóvoa, José A; Loureiro-Ga, Marcos; Jiménez, Víctor; Baz, José Antonio; Íñiguez, Andrés

Busto, Laura; Veiga, César; González-Nóvoa, José A; Loureiro-Ga, Marcos; Jiménez, Víctor; Baz, José Antonio; Íñiguez, Andrés.

Afiliação

Busto L; Cardiovascular Research Group, Galicia Sur Health Research Institute (IIS Galicia Sur), 36213 Vigo, Spain.
Veiga C; Cardiovascular Research Group, Galicia Sur Health Research Institute (IIS Galicia Sur), 36213 Vigo, Spain.
González-Nóvoa JA; Cardiovascular Research Group, Galicia Sur Health Research Institute (IIS Galicia Sur), 36213 Vigo, Spain.
Loureiro-Ga M; Cardiovascular Research Group, Galicia Sur Health Research Institute (IIS Galicia Sur), 36213 Vigo, Spain.
Jiménez V; Cardiology Department, Complexo Hospitalario Universitario de Vigo (SERGAS), Álvaro Cunqueiro Hospital, 36213 Vigo, Spain.
Baz JA; Cardiology Department, Complexo Hospitalario Universitario de Vigo (SERGAS), Álvaro Cunqueiro Hospital, 36213 Vigo, Spain.
Íñiguez A; Cardiology Department, Complexo Hospitalario Universitario de Vigo (SERGAS), Álvaro Cunqueiro Hospital, 36213 Vigo, Spain.

Diagnostics (Basel) ; 12(2)2022 Jan 27.

Article em En | MEDLINE | ID: mdl-35204425

Palavras-chave

U-Net; angiography; deep learning; segmentation; transcatheter aortic valve implantation (TAVI)

Texto completo

Imprimir

XML

PubMed Links

Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Revista: Diagnostics (Basel) Ano de publicação: 2022 Tipo de documento: Article

Texto completo

Imprimir

XML

PubMed Links

Buscar no Google