Approaching automated applicator digitization from a new angle: Using sagittal images to improve deep learning accuracy and robustness in high-dose-rate prostate brachytherapy.

Weishaupt, Luca Leon; Sayed, Hisham Kamal; Mao, Ximeng; Choo, Richard; Stish, Bradley J; Enger, Shirin A; Deufel, Christopher

Weishaupt, Luca Leon; Sayed, Hisham Kamal; Mao, Ximeng; Choo, Richard; Stish, Bradley J; Enger, Shirin A; Deufel, Christopher.

Afiliación

Weishaupt LL; Radiation Oncology, Mayo Clinic, Rochester, MN; Medical Physics Unit, McGill University, Montreal, Quebec, Canada.
Sayed HK; Radiation Oncology, Mayo Clinic, Rochester, MN; Inova Schar Cancer Institute, Fairfax, VA.
Mao X; Mila - Quebec AI Institute, Montréal, Quebec, Canada.
Choo R; Radiation Oncology, Mayo Clinic, Rochester, MN.
Stish BJ; Radiation Oncology, Mayo Clinic, Rochester, MN.
Enger SA; Medical Physics Unit, McGill University, Montreal, Quebec, Canada; Research Institute, McGill University Health Center, Montreal, Quebec, Canada; Lady Davis Institute for Medical Research, Jewish General Hospital, Montréal, Quebec, Canada.
Deufel C; Radiation Oncology, Mayo Clinic, Rochester, MN. Electronic address: deufel.christopher@mayo.edu.

Brachytherapy ; 21(4): 520-531, 2022.

Article en En | MEDLINE | ID: mdl-35422402

Asunto(s)

Braquiterapia; Aprendizaje Profundo; Braquiterapia/métodos; Humanos; Masculino; Próstata; Estudios Retrospectivos; Tomografía Computarizada por Rayos X/métodos

Palabras clave

Applicator digitization; Brachytherapy; Deep learning; Prostate; Segmentation

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Braquiterapia / Aprendizaje Profundo Tipo de estudio: Guideline / Observational_studies Límite: Humans / Male Idioma: En Revista: Brachytherapy Asunto de la revista: RADIOTERAPIA Año: 2022 Tipo del documento: Article País de afiliación: Canadá

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