Prediction of the position of external markers using a recurrent neural network trained with unbiased online recurrent optimization for safe lung cancer radiotherapy.

Pohl, Michel; Uesaka, Mitsuru; Takahashi, Hiroyuki; Demachi, Kazuyuki; Bhusal Chhatkuli, Ritu

Pohl, Michel; Uesaka, Mitsuru; Takahashi, Hiroyuki; Demachi, Kazuyuki; Bhusal Chhatkuli, Ritu.

Afiliação

Pohl M; The University of Tokyo, 113-8654 Tokyo, Japan. Electronic address: michel.pohl@centrale-marseille.fr.
Uesaka M; Japan Atomic Energy Commission, 100-8914 Tokyo, Japan.
Takahashi H; The University of Tokyo, 113-8654 Tokyo, Japan.
Demachi K; The University of Tokyo, 113-8654 Tokyo, Japan.
Bhusal Chhatkuli R; National Institutes for Quantum and Radiological Science and Technology, 263-8555 Chiba, Japan.

Comput Methods Programs Biomed ; 222: 106908, 2022 Jul.

Article em En | MEDLINE | ID: mdl-35716534

Assuntos

Neoplasias Pulmonares; Redes Neurais de Computação; Algoritmos; Humanos; Pulmão; Neoplasias Pulmonares/radioterapia; Movimento (Física); Respiração

Palavras-chave

Lung cancer; Online learning; Radiotherapy; Recurrent neural network; Respiratory motion management; Time series forecasting

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Redes Neurais de Computação / Neoplasias Pulmonares Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article

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