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Segmentation and Classification of Glaucoma Using U-Net with Deep Learning Model.
Sudhan, M B; Sinthuja, M; Pravinth Raja, S; Amutharaj, J; Charlyn Pushpa Latha, G; Sheeba Rachel, S; Anitha, T; Rajendran, T; Waji, Yosef Asrat.
Affiliation
  • Sudhan MB; Department of Artificial Intelligence and Machine Learning, MVJ College of Engineering, Bangalore, Karnataka, India.
  • Sinthuja M; Department of Information Science and Engineering, M. S. Ramaiah Institute of Technology, Bangalore, Karnataka, India.
  • Pravinth Raja S; Department of Computer Science & Engineering, Presidency University, Bangalore, Karnataka, India.
  • Amutharaj J; Department of Information Science and Engineering, RajaRajeswari College of Engineering, Mysore Road, Bangalore, Karnataka, India.
  • Charlyn Pushpa Latha G; Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences (Deemed to be University), Chennai, Tamilnadu, India.
  • Sheeba Rachel S; Department of Information Technology, Sri Sairam Engineering College (Autonomous), Chennai, Tamilnadu, India.
  • Anitha T; Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences (Deemed to be University), Chennai, Tamilnadu, India.
  • Rajendran T; Makeit Technologies, Coimbatore, Tamilnadu, India.
  • Waji YA; Department of Chemical Engineering, College of Biological and Chemical Engineering Addis Ababa Science and Technology University, Addis Ababa, Ethiopia.
J Healthc Eng ; 2022: 1601354, 2022.
Article in En | MEDLINE | ID: mdl-35222876

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Optic Disk / Glaucoma / Deep Learning Type of study: Prognostic_studies / Screening_studies Limits: Humans Language: En Journal: J Healthc Eng Year: 2022 Document type: Article Affiliation country: India Country of publication: United kingdom

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Optic Disk / Glaucoma / Deep Learning Type of study: Prognostic_studies / Screening_studies Limits: Humans Language: En Journal: J Healthc Eng Year: 2022 Document type: Article Affiliation country: India Country of publication: United kingdom