Development of convolutional neural network model for diagnosing meniscus tear using magnetic resonance image.

Shin, Hyunkwang; Choi, Gyu Sang; Shon, Oog-Jin; Kim, Gi Beom; Chang, Min Cheol

Shin, Hyunkwang; Choi, Gyu Sang; Shon, Oog-Jin; Kim, Gi Beom; Chang, Min Cheol.

Afiliación

Shin H; Department of Information and Communication Engineering, Yeungnam University, Gyeongsan-si, Republic of Korea.
Choi GS; Department of Information and Communication Engineering, Yeungnam University, Gyeongsan-si, Republic of Korea.
Shon OJ; Department of Orthopedic Surgery, Yeungnam University College of Medicine, Yeungnam University, 317-1, Daemyungdong, Namku, Daegu, 42415, Republic of Korea.
Kim GB; Department of Orthopedic Surgery, Yeungnam University College of Medicine, Yeungnam University, 317-1, Daemyungdong, Namku, Daegu, 42415, Republic of Korea. donggamgb@hanmail.net.
Chang MC; Department of Physical Medicine and Rehabilitation, College of Medicine, Yeungnam University, 317-1, Daemyungdong, Namku, Daegu, 42415, Republic of Korea. wheel633@gmail.com.

BMC Musculoskelet Disord ; 23(1): 510, 2022 May 30.

Article en En | MEDLINE | ID: mdl-35637451

Asunto(s)

Traumatismos de la Rodilla; Lesiones de Menisco Tibial; Humanos; Traumatismos de la Rodilla/diagnóstico; Imagen por Resonancia Magnética/métodos; Meniscos Tibiales/patología; Redes Neurales de la Computación; Estudios Retrospectivos; Rotura/patología; Lesiones de Menisco Tibial/diagnóstico por imagen; Lesiones de Menisco Tibial/patología

Palabras clave

Convolutional neural network; Deep learning; Knee; Magnetic resonance imaging; Meniscus tear

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Lesiones de Menisco Tibial / Traumatismos de la Rodilla Tipo de estudio: Diagnostic_studies / Observational_studies / Prognostic_studies Límite: Humans Idioma: En Revista: BMC Musculoskelet Disord Asunto de la revista: FISIOLOGIA / ORTOPEDIA Año: 2022 Tipo del documento: Article Pais de publicación: Reino Unido

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