Deep learning-based approach for the automatic segmentation of adult and pediatric temporal bone computed tomography images.

Ke, Jia; Lv, Yi; Ma, Furong; Du, Yali; Xiong, Shan; Wang, Junchen; Wang, Jiang

Ke, Jia; Lv, Yi; Ma, Furong; Du, Yali; Xiong, Shan; Wang, Junchen; Wang, Jiang.

Afiliación

Ke J; Department of Otorhinolaryngology-Head and Neck Surgery, Peking University Third Hospital, Peking University, Beijing, China.
Lv Y; School of Mechanical Engineering and Automation, Beihang University, Beijing, China.
Ma F; North China Research Institute of Electro-optics, Beijing, China.
Du Y; Department of Otorhinolaryngology-Head and Neck Surgery, Peking University Third Hospital, Peking University, Beijing, China.
Xiong S; Department of Otorhinolaryngology-Head and Neck Surgery, Peking University Third Hospital, Peking University, Beijing, China.
Wang J; Department of Otorhinolaryngology-Head and Neck Surgery, Peking University Third Hospital, Peking University, Beijing, China.
Wang J; School of Mechanical Engineering and Automation, Beihang University, Beijing, China.

Quant Imaging Med Surg ; 13(3): 1577-1591, 2023 Mar 01.

Article en En | MEDLINE | ID: mdl-36915310

Palabras clave

Deep learning; accuracy; adults and children; automatic segmentation; temporal bone computed tomography

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Quant Imaging Med Surg Año: 2023 Tipo del documento: Article País de afiliación: China Pais de publicación: China

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