Auto-detection and segmentation of involved lymph nodes in HPV-associated oropharyngeal cancer using a convolutional deep learning neural network.

Taku, Nicolette; Wahid, Kareem A; van Dijk, Lisanne V; Sahlsten, Jaakko; Jaskari, Joel; Kaski, Kimmo; Fuller, Clifton D; Naser, Mohamed A

Taku, Nicolette; Wahid, Kareem A; van Dijk, Lisanne V; Sahlsten, Jaakko; Jaskari, Joel; Kaski, Kimmo; Fuller, Clifton D; Naser, Mohamed A.

Afiliación

Taku N; Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States.
Wahid KA; Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States.
van Dijk LV; Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States.
Sahlsten J; Department of Radiation Oncology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands.
Jaskari J; Aalto University School of Science, Aalto, Finland.
Kaski K; Aalto University School of Science, Aalto, Finland.
Fuller CD; Department of Radiation Oncology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands.
Naser MA; Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States.

Clin Transl Radiat Oncol ; 36: 47-55, 2022 Sep.

Article en En | MEDLINE | ID: mdl-35782963

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Clin Transl Radiat Oncol Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos

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