Learning from pseudo-labels: deep networks improve consistency in longitudinal brain volume estimation.

Zhan, Geng; Wang, Dongang; Cabezas, Mariano; Bai, Lei; Kyle, Kain; Ouyang, Wanli; Barnett, Michael; Wang, Chenyu

Zhan, Geng; Wang, Dongang; Cabezas, Mariano; Bai, Lei; Kyle, Kain; Ouyang, Wanli; Barnett, Michael; Wang, Chenyu.

Afiliación

Zhan G; Brain and Mind Center, The University of Sydney, Sydney, NSW, Australia.
Wang D; Sydney Neuroimaging Analysis Center, Sydney, NSW, Australia.
Cabezas M; Brain and Mind Center, The University of Sydney, Sydney, NSW, Australia.
Bai L; Sydney Neuroimaging Analysis Center, Sydney, NSW, Australia.
Kyle K; Brain and Mind Center, The University of Sydney, Sydney, NSW, Australia.
Ouyang W; Shanghai AI Laboratory, Shanghai, China.
Barnett M; Brain and Mind Center, The University of Sydney, Sydney, NSW, Australia.
Wang C; Sydney Neuroimaging Analysis Center, Sydney, NSW, Australia.

Front Neurosci ; 17: 1196087, 2023.

Article en En | MEDLINE | ID: mdl-37483345

Palabras clave

MRI; atrophy measurement; brain volume change; deep learning; longitudinal analysis; multiple sclerosis

Texto completo

Añadir a Mi BVS

Imprimir

XML

PubMed Links

Buscar en Google

Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Front Neurosci Año: 2023 Tipo del documento: Article País de afiliación: Australia

Texto completo

Añadir a Mi BVS

Imprimir

XML

PubMed Links

Buscar en Google