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Machine learning for lung CT texture analysis: Improvement of inter-observer agreement for radiological finding classification in patients with pulmonary diseases.
Ohno, Yoshiharu; Aoyagi, Kota; Takenaka, Daisuke; Yoshikawa, Takeshi; Ikezaki, Aina; Fujisawa, Yasuko; Murayama, Kazuhiro; Hattori, Hidekazu; Toyama, Hiroshi.
Afiliación
  • Ohno Y; Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan; Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Aichi, Japan; Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kob
  • Aoyagi K; Canon Medical Systems Corporation, Otawara, Tochigi, Japan.
  • Takenaka D; Department of Diagnostic Radiology, Hyogo Cancer Center, Akashi, Hyogo, Japan.
  • Yoshikawa T; Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan; Department of Diagnostic Radiology, Hyogo Cancer Center, Akashi, Hyogo, Japan.
  • Ikezaki A; Canon Medical Systems Corporation, Otawara, Tochigi, Japan.
  • Fujisawa Y; Canon Medical Systems Corporation, Otawara, Tochigi, Japan.
  • Murayama K; Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Aichi, Japan.
  • Hattori H; Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan.
  • Toyama H; Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan.
Eur J Radiol ; 134: 109410, 2021 Jan.
Article en En | MEDLINE | ID: mdl-33246272

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Tomografía Computarizada por Rayos X / Enfermedades Pulmonares Intersticiales Tipo de estudio: Diagnostic_studies Límite: Humans Idioma: En Revista: Eur J Radiol Año: 2021 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Tomografía Computarizada por Rayos X / Enfermedades Pulmonares Intersticiales Tipo de estudio: Diagnostic_studies Límite: Humans Idioma: En Revista: Eur J Radiol Año: 2021 Tipo del documento: Article