Deep learning-based quantitative estimation of lymphedema-induced fibrosis using three-dimensional computed tomography images.

Son, Hyewon; Lee, Suwon; Kim, Kwangsoo; Koo, Kyo-In; Hwang, Chang Ho

Son, Hyewon; Lee, Suwon; Kim, Kwangsoo; Koo, Kyo-In; Hwang, Chang Ho.

Afiliación

Son H; Major of Biomedical Engineering, Department of Electrical, Electronic and Computer Engineering, University of Ulsan, Nam-gu, Ulsan, 44610, Republic of Korea.
Lee S; Major of Biomedical Engineering, Department of Electrical, Electronic and Computer Engineering, University of Ulsan, Nam-gu, Ulsan, 44610, Republic of Korea.
Kim K; Department of Electronic Engineering, Hanbat National University, Yuseong-gu, Daejeon, 34158, Republic of Korea.
Koo KI; Major of Biomedical Engineering, Department of Electrical, Electronic and Computer Engineering, University of Ulsan, Nam-gu, Ulsan, 44610, Republic of Korea. kikoo@ulsan.ac.kr.
Hwang CH; Department of Physical & Rehabilitation Medicine, Chungnam National University Sejong Hospital, College of Medicine, Chungnam National University, 20 Bodeum 7-ro, Sejong, 30099, Republic of Korea. chhwang1220@cnu.ac.kr.

Sci Rep ; 12(1): 15371, 2022 09 13.

Article en En | MEDLINE | ID: mdl-36100619

Asunto(s)

Aprendizaje Profundo; Linfedema; Estudios Transversales; Fibrosis; Humanos; Linfedema/diagnóstico por imagen; Linfedema/etiología; Tomografía Computarizada por Rayos X/métodos

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Aprendizaje Profundo / Linfedema Tipo de estudio: Etiology_studies / Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Sci Rep Año: 2022 Tipo del documento: Article

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