Assessing red blood cell deformability from microscopy images using deep learning.

Lamoureux, Erik S; Islamzada, Emel; Wiens, Matthew V J; Matthews, Kerryn; Duffy, Simon P; Ma, Hongshen

Lamoureux, Erik S; Islamzada, Emel; Wiens, Matthew V J; Matthews, Kerryn; Duffy, Simon P; Ma, Hongshen.

Afiliação

Lamoureux ES; Department of Mechanical Engineering, University of British Columbia, 2054-6250 Applied Science Lane, Vancouver, BC, V6T 1Z4, Canada. hongma@mech.ubc.ca.
Islamzada E; Centre for Blood Research, University of British Columbia, Vancouver, BC, Canada.
Wiens MVJ; Centre for Blood Research, University of British Columbia, Vancouver, BC, Canada.
Matthews K; Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada.
Duffy SP; School of Biomedical Engineering, University of British Columbia, Vancouver, BC, Canada.
Ma H; Department of Mechanical Engineering, University of British Columbia, 2054-6250 Applied Science Lane, Vancouver, BC, V6T 1Z4, Canada. hongma@mech.ubc.ca.

Lab Chip ; 22(1): 26-39, 2021 12 21.

Article em En | MEDLINE | ID: mdl-34874395

Assuntos

Aprendizado Profundo; Microscopia; Contagem de Eritrócitos; Deformação Eritrocítica; Eritrócitos; Humanos

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Aprendizado Profundo / Microscopia Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article

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