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Detection of urinary tract calculi on CT images reconstructed with deep learning algorithms.
Thapaliya, Samjhana; Brady, Samuel L; Somasundaram, Elanchezhian; Anton, Christopher G; Coley, Brian D; Towbin, Alexander J; Zhang, Bin; Dillman, Jonathan R; Trout, Andrew T.
Afiliación
  • Thapaliya S; Department of Radiology, Cincinnati Children's Hospital Medical Center, 3333 Burnet Avenue, MLC 5031, Cincinnati, OH, 45229, USA.
  • Brady SL; Department of Radiology, Cincinnati Children's Hospital Medical Center, 3333 Burnet Avenue, MLC 5031, Cincinnati, OH, 45229, USA.
  • Somasundaram E; Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, OH, USA.
  • Anton CG; Department of Radiology, Cincinnati Children's Hospital Medical Center, 3333 Burnet Avenue, MLC 5031, Cincinnati, OH, 45229, USA.
  • Coley BD; Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, OH, USA.
  • Towbin AJ; Department of Radiology, Cincinnati Children's Hospital Medical Center, 3333 Burnet Avenue, MLC 5031, Cincinnati, OH, 45229, USA.
  • Zhang B; Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, OH, USA.
  • Dillman JR; Department of Radiology, Cincinnati Children's Hospital Medical Center, 3333 Burnet Avenue, MLC 5031, Cincinnati, OH, 45229, USA.
  • Trout AT; Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, OH, USA.
Abdom Radiol (NY) ; 47(1): 265-271, 2022 01.
Article en En | MEDLINE | ID: mdl-34605964
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Sistema Urinario / Cálculos Urinarios / Aprendizaje Profundo Tipo de estudio: Diagnostic_studies / Observational_studies Límite: Adolescent / Adult / Child / Female / Humans / Male Idioma: En Revista: Abdom Radiol (NY) Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos
Texto completo
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PubMed Links
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Sistema Urinario / Cálculos Urinarios / Aprendizaje Profundo Tipo de estudio: Diagnostic_studies / Observational_studies Límite: Adolescent / Adult / Child / Female / Humans / Male Idioma: En Revista: Abdom Radiol (NY) Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos