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Fully automatic deep learning-based lung parenchyma segmentation and boundary correction in thoracic CT scans.
Rikhari, Himanshu; Baidya Kayal, Esha; Ganguly, Shuvadeep; Sasi, Archana; Sharma, Swetambri; Dheeksha, D S; Saini, Manish; Rangarajan, Krithika; Bakhshi, Sameer; Kandasamy, Devasenathipathy; Mehndiratta, Amit.
Afiliação
  • Rikhari H; Centre for Biomedical Engineering, Indian Institute of Technology Delhi, New Delhi, India.
  • Baidya Kayal E; Centre for Biomedical Engineering, Indian Institute of Technology Delhi, New Delhi, India.
  • Ganguly S; All India Institute of Medical Sciences New Delhi, Medical Oncology, Dr. B.R.A. IRCH, New Delhi, India.
  • Sasi A; All India Institute of Medical Sciences New Delhi, Medical Oncology, Dr. B.R.A. IRCH, New Delhi, India.
  • Sharma S; All India Institute of Medical Sciences New Delhi, Medical Oncology, Dr. B.R.A. IRCH, New Delhi, India.
  • Dheeksha DS; Radiodiagnosis, All India Institute of Medical Sciences New Delhi, New Delhi, India.
  • Saini M; Radiodiagnosis, All India Institute of Medical Sciences New Delhi, New Delhi, India.
  • Rangarajan K; Radiodiagnosis, All India Institute of Medical Sciences New Delhi, Dr. B.R.A. IRCH, New Delhi, India.
  • Bakhshi S; All India Institute of Medical Sciences New Delhi, Medical Oncology, Dr. B.R.A. IRCH, New Delhi, India.
  • Kandasamy D; Radiodiagnosis, All India Institute of Medical Sciences New Delhi, New Delhi, India.
  • Mehndiratta A; Centre for Biomedical Engineering, Indian Institute of Technology Delhi, New Delhi, India. amit.mehndiratta@keble.oxon.org.
Int J Comput Assist Radiol Surg ; 19(2): 261-272, 2024 Feb.
Article em En | MEDLINE | ID: mdl-37594684
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Aprendizado Profundo Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Int J Comput Assist Radiol Surg Assunto da revista: RADIOLOGIA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Índia
Texto completo
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Aprendizado Profundo Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Int J Comput Assist Radiol Surg Assunto da revista: RADIOLOGIA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Índia