Patient-specific three-dimensional dose distribution prediction via deep learning for prostate cancer therapy: Improvement with the structure loss.

Koike, Yuhei; Takegawa, Hideki; Anetai, Yusuke; Ohira, Shingo; Nakamura, Satoaki; Tanigawa, Noboru

Koike, Yuhei; Takegawa, Hideki; Anetai, Yusuke; Ohira, Shingo; Nakamura, Satoaki; Tanigawa, Noboru.

Afiliação

Koike Y; Department of Radiology, Kansai Medical University, 2-5-1 Shinmachi, Hirakata, Osaka 573-1010, Japan. Electronic address: koikeyuh@hirakata.kmu.ac.jp.
Takegawa H; Department of Radiology, Kansai Medical University, 2-5-1 Shinmachi, Hirakata, Osaka 573-1010, Japan.
Anetai Y; Department of Radiology, Kansai Medical University, 2-5-1 Shinmachi, Hirakata, Osaka 573-1010, Japan.
Ohira S; Department of Radiation Oncology, Osaka International Cancer Institute, 3-1-69 Otemae, Chuo-ku, Osaka 537-8567, Japan.
Nakamura S; Department of Radiology, Kansai Medical University, 2-5-1 Shinmachi, Hirakata, Osaka 573-1010, Japan.
Tanigawa N; Department of Radiology, Kansai Medical University, 2-5-1 Shinmachi, Hirakata, Osaka 573-1010, Japan.

Phys Med ; 107: 102544, 2023 Mar.

Article em En | MEDLINE | ID: mdl-36774846

Assuntos

Aprendizado Profundo; Neoplasias da Próstata; Radioterapia de Intensidade Modulada; Masculino; Humanos; Próstata; Dosagem Radioterapêutica; Radioterapia de Intensidade Modulada/métodos; Planejamento da Radioterapia Assistida por Computador/métodos; Neoplasias da Próstata/diagnóstico por imagem; Neoplasias da Próstata/radioterapia

Palavras-chave

Deep learning; Patient-specific dose distribution; Prostate cancer; VMAT

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans / Male Idioma: En Ano de publicação: 2023 Tipo de documento: Article

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