Personnel Information

写真a

Oda Goshi


Job title

Junior Associate Professor

Campus Career 【 display / non-display

  • 2014.12
    -
    Now
    Tokyo Medical and Dental University, Graduate School of Medical and Dental Sciences, Medical and Dental Sciences, Systemic Organ Regulation, Specialized Surgeries, Assistant Professor
  • 2015.04
    -
    2017.03
    Tokyo Medical and Dental University, Medical Hospital, Hospital Departments, Departments of Surgery, Breast Surgery, Assistant Professor
  • 2017.04
    -
    2017.06
    Tokyo Medical and Dental University, Medical Hospital, Hospital Departments, Departments of Surgery, Breast Surgery, Assistant Professor
  • 2017.07
    -
    2018.03
    Tokyo Medical and Dental University, Medical Hospital, Central Clinical Facilities, Medical Informatics, Junior Associate Professor
  • 2018.04
    -
    Now
    Tokyo Medical and Dental University, Medical Hospital, Central Clinical Facilities, Medical Informatics, Junior Associate Professor
 

Published Papers & Misc 【 display / non-display

  • Tomoyuki Fujioka, Mio Mori, Kazunori Kubota, Yuka Kikuchi, Leona Katsuta, Mio Adachi, Goshi Oda, Tsuyoshi Nakagawa, Yoshio Kitazume, Ukihide Tateishi. Breast Ultrasound Image Synthesis using Deep Convolutional Generative Adversarial Networks. Diagnostics (Basel). 2019.11; 9 (4): ( PubMed, DOI )

  • Fujioka T, Mori M, Kubota K, Kikuchi Y, Katsuta L, Kasahara M, Oda G, Ishiba T, Nakagawa T, Tateishi U. Simultaneous comparison between strain and shear wave elastography of breast masses for the differentiation of benign and malignant lesions by qualitative and quantitative assessments. Breast cancer (Tokyo, Japan). 2019.06; ( PubMed, DOI )

  • Fujioka T, Kubota K, Kikuchi Y, Tsuchiya J, Tateishi U, Kasaharak M, Oda G, Ishiba T, Nakagawa T. The feasibility of using 18F-FDG-PET/CT in patients with mucinous breast carcinoma. Nuclear medicine communications. 2018.09; ( PubMed, DOI )

  • Fujioka T, Kubota K, Mori M, Kikuchi Y, Katsuta L, Kasahara M, Oda G, Ishiba T, Nakagawa T, Tateishi U. Distinction between benign and malignant breast masses at breast ultrasound using deep learning method with convolutional neural network. Japanese journal of radiology. 2019.03; ( PubMed, DOI )