Application of multiple deep learning models for automatic burn wound assessment.

Chang, Che Wei; Ho, Chun Yee; Lai, Feipei; Christian, Mesakh; Huang, Shih Chen; Chang, Dun Hao; Chen, Yo Shen

Chang, Che Wei; Ho, Chun Yee; Lai, Feipei; Christian, Mesakh; Huang, Shih Chen; Chang, Dun Hao; Chen, Yo Shen.

Afiliação

Chang CW; Graduate Institute of Biomedical Electronics & Bioinformatics, National Taiwan University, Taipei, Taiwan; Division of Plastic and Reconstructive Surgery, Department of Surgery, Far Eastern Memorial Hospital, New Taipei, Taiwan. Electronic address: b92401068@gmail.com.
Ho CY; Division of Plastic and Reconstructive Surgery, Department of Surgery, Far Eastern Memorial Hospital, New Taipei, Taiwan.
Lai F; Graduate Institute of Biomedical Electronics & Bioinformatics, National Taiwan University, Taipei, Taiwan; Department of Computer Science & Information Engineering, National Taiwan University, Taipei, Taiwan.
Christian M; Department of Computer Science & Information Engineering, National Taiwan University, Taipei, Taiwan.
Huang SC; Division of Plastic and Reconstructive Surgery, Department of Surgery, Far Eastern Memorial Hospital, New Taipei, Taiwan.
Chang DH; Division of Plastic and Reconstructive Surgery, Department of Surgery, Far Eastern Memorial Hospital, New Taipei, Taiwan; Department of Information Management, Yuan Ze University, Taiwan.
Chen YS; Division of Plastic and Reconstructive Surgery, Department of Surgery, Far Eastern Memorial Hospital, New Taipei, Taiwan.

Burns ; 49(5): 1039-1051, 2023 Aug.

Article em En | MEDLINE | ID: mdl-35945064

Assuntos

Queimaduras; Aprendizado Profundo; Humanos; Queimaduras/diagnóstico; Inteligência Artificial; Hidratação/métodos; Superfície Corporal

Palavras-chave

% TBSA burned; Burn wound segmentation; Deep burn segmentation; Deep learning; Machine learning; Rule of palm

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Queimaduras / Aprendizado Profundo Limite: Humans Idioma: En Revista: Burns Assunto da revista: TRAUMATOLOGIA Ano de publicação: 2023 Tipo de documento: Article

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