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Deep Learning Reconstruction to Improve the Quality of MR Imaging: Evaluating the Best Sequence for T-category Assessment in Non-small Cell Lung Cancer Patients.
Takenaka, Daisuke; Ozawa, Yoshiyuki; Yamamoto, Kaori; Shinohara, Maiko; Ikedo, Masato; Yui, Masao; Oshima, Yuka; Hamabuchi, Nayu; Nagata, Hiroyuki; Ueda, Takahiro; Ikeda, Hirotaka; Iwase, Akiyoshi; Yoshikawa, Takeshi; Toyama, Hiroshi; Ohno, Yoshiharu.
Affiliation
  • Takenaka D; Department of Radiology, Fujita Health University School of Medicine.
  • Ozawa Y; Department of Diagnostic Radiology, Hyogo Cancer Center.
  • Yamamoto K; Department of Radiology, Fujita Health University School of Medicine.
  • Shinohara M; Canon Medical Systems Corporation.
  • Ikedo M; Canon Medical Systems Corporation.
  • Yui M; Canon Medical Systems Corporation.
  • Oshima Y; Canon Medical Systems Corporation.
  • Hamabuchi N; Department of Radiology, Fujita Health University School of Medicine.
  • Nagata H; Department of Radiology, Fujita Health University School of Medicine.
  • Ueda T; Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine.
  • Ikeda H; Department of Radiology, Fujita Health University School of Medicine.
  • Iwase A; Department of Radiology, Fujita Health University School of Medicine.
  • Yoshikawa T; Department of Radiology, Fujita Health University Hospital.
  • Toyama H; Department of Radiology, Fujita Health University School of Medicine.
  • Ohno Y; Department of Diagnostic Radiology, Hyogo Cancer Center.
Magn Reson Med Sci ; 2023 Sep 01.
Article in En | MEDLINE | ID: mdl-37661425

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Magn Reson Med Sci Journal subject: DIAGNOSTICO POR IMAGEM Year: 2023 Document type: Article Country of publication: Japan

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Magn Reson Med Sci Journal subject: DIAGNOSTICO POR IMAGEM Year: 2023 Document type: Article Country of publication: Japan