Machine Learning-Based Quality Assurance for Automatic Segmentation of Head-and-Neck Organs-at-Risk in Radiotherapy.

Luan, Shunyao; Xue, Xudong; Wei, Changchao; Ding, Yi; Zhu, Benpeng; Wei, Wei

Luan, Shunyao; Xue, Xudong; Wei, Changchao; Ding, Yi; Zhu, Benpeng; Wei, Wei.

Afiliación

Luan S; Department of Radiation Oncology, 117922Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Xue X; School of Optical and Electronic Information, 12443Huazhong University of Science and Technology, Wuhan, China.
Wei C; Department of Radiation Oncology, 117922Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Ding Y; Department of Radiation Oncology, 117922Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Zhu B; Key Laboratory of Artificial Micro and Nano-structures of Ministry of Education, Center for Theoretical Physics, School of Physics and Technology, 12390Wuhan University, Wuhan, China.
Wei W; Department of Radiation Oncology, 117922Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.

Technol Cancer Res Treat ; 22: 15330338231157936, 2023.

Article en En | MEDLINE | ID: mdl-36788411

Asunto(s)

Procesamiento de Imagen Asistido por Computador; Tomografía Computarizada por Rayos X; Humanos; Procesamiento de Imagen Asistido por Computador/métodos; Redes Neurales de la Computación; Cuello; Aprendizaje Automático

Palabras clave

automatic segmentation; deep learning; head and neck; machine learning; quality assurance; radiotherapy

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Procesamiento de Imagen Asistido por Computador / Tomografía Computarizada por Rayos X Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Technol Cancer Res Treat Asunto de la revista: NEOPLASIAS / TERAPEUTICA Año: 2023 Tipo del documento: Article País de afiliación: China Pais de publicación: Estados Unidos

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