A deep learning framework for automatic detection of arbitrarily shaped fiducial markers in intrafraction fluoroscopic images.

Mylonas, Adam; Keall, Paul J; Booth, Jeremy T; Shieh, Chun-Chien; Eade, Thomas; Poulsen, Per Rugaard; Nguyen, Doan Trang

Mylonas, Adam; Keall, Paul J; Booth, Jeremy T; Shieh, Chun-Chien; Eade, Thomas; Poulsen, Per Rugaard; Nguyen, Doan Trang.

Afiliação

Mylonas A; Faculty of Medicine and Health, ACRF Image X Institute, The University of Sydney, Sydney, NSW, Australia.
Keall PJ; Faculty of Medicine and Health, ACRF Image X Institute, The University of Sydney, Sydney, NSW, Australia.
Booth JT; Royal North Shore Hospital, Northern Sydney Cancer Centre, St Leonards, NSW, Australia.
Shieh CC; Faculty of Medicine and Health, ACRF Image X Institute, The University of Sydney, Sydney, NSW, Australia.
Eade T; Royal North Shore Hospital, Northern Sydney Cancer Centre, St Leonards, NSW, Australia.
Poulsen PR; Department of Oncology, Aarhus University Hospital, 8000, Aarhus, Denmark.
Nguyen DT; Faculty of Medicine and Health, ACRF Image X Institute, The University of Sydney, Sydney, NSW, Australia.

Med Phys ; 46(5): 2286-2297, 2019 May.

Article em En | MEDLINE | ID: mdl-30929254

Assuntos

Aprendizado Profundo; Fracionamento da Dose de Radiação; Marcadores Fiduciais; Fluoroscopia/normas; Radioterapia Guiada por Imagem; Automação; Humanos; Masculino; Neoplasias da Próstata/diagnóstico por imagem; Neoplasias da Próstata/radioterapia

Palavras-chave

convolutional neural network (CNN); deep learning; fiducial marker detection; image-guided radiation therapy (IGRT)

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Fluoroscopia / Fracionamento da Dose de Radiação / Marcadores Fiduciais / Radioterapia Guiada por Imagem / Aprendizado Profundo Idioma: En Ano de publicação: 2019 Tipo de documento: Article

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