Comprehensive Assessment of Fine-Grained Wound Images Using a Patch-Based CNN With Context-Preserving Attention.

Liu, Ziyang; Agu, Emmanuel; Pedersen, Peder; Lindsay, Clifford; Tulu, Bengisu; Strong, Diane

Liu, Ziyang; Agu, Emmanuel; Pedersen, Peder; Lindsay, Clifford; Tulu, Bengisu; Strong, Diane.

Afiliación

Liu Z; Computer Science Department, Worcester Polytechnic Institute, Worcester, MA 01609 USA.
Agu E; Computer Science Department, Worcester Polytechnic Institute, Worcester, MA 01609 USA.
Pedersen P; Electrical and Computer Engineering Department, Worcester Polytechnic Institute, Worcester, MA 01609 USA.
Lindsay C; Department of Radiology, University of Massachusetts Medical School, Worcester, MA 01655 USA.
Tulu B; Foisie Business School, Worcester Polytechnic Institute, Worcester, MA 01609 USA.
Strong D; Foisie Business School, Worcester Polytechnic Institute, Worcester, MA 01609 USA.

IEEE Open J Eng Med Biol ; 2: 224-234, 2021.

Article en En | MEDLINE | ID: mdl-34532712

Palabras clave

Chronic wounds; deep learning; medical imaging; smartphone assessment; transfer learning

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Guideline / Prognostic_studies Idioma: En Revista: IEEE Open J Eng Med Biol Año: 2021 Tipo del documento: Article Pais de publicación: Estados Unidos

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