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Saka Tomoki  坂 知樹

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坂 知樹  サカ トモキ

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Researcher Number 60826577
Other IDs
Affiliation (Current) 2026: 東京電機大学, システム デザイン 工学部, 助教
Affiliation (based on the past Project Information) *help 2023 – 2024: 東京電機大学, システム デザイン 工学部, 助教
Review Section/Research Field
Principal Investigator
Basic Section 62010:Life, health and medical informatics-related
Keywords
Principal Investigator
肺血流 / 多入力系ファントム / AI血流解析 / 深層学習Perfusion / モデルなし手法 / 多入力解析 / 深層学習 / Convolution法 / 肺血流解析 / Perfusion
  • Research Projects

    (1 results)
  • Research Products

    (3 results)
  •  AI血流解析を用いたコロナ後遺症の病態解明Principal Investigator

    • Principal Investigator
      坂 知樹
    • Project Period (FY)
      2023 – 2025
    • Research Category
      Grant-in-Aid for Early-Career Scientists
    • Review Section
      Basic Section 62010:Life, health and medical informatics-related
    • Research Institution
      Tokyo Denki University

All 2024 2023

All Journal Article Presentation

  • [Journal Article] Model-Free Multi-Input Perfusion Using Deep Learning Algorithm2024

    • Author(s)
      坂 知樹、岩澤 多恵
    • Journal Title

      Medical Imaging Technology

      Volume: 42 Issue: 5 Pages: 145-154

    • DOI

      10.11409/mit.42.145

    • ISSN
      0288-450X, 2185-3193
    • Year and Date
      2024-11-25
    • Language
      Japanese
    • Data Source
      KAKENHI-PROJECT-23K16998
  • [Journal Article] Model-less Perfusion Analysis using Deep Learning Framework2023

    • Author(s)
      Saka Tomoki、Iwasawa Tae、Tsuzuki Marcos S.G.
    • Journal Title

      IFAC-PapersOnLine

      Volume: 56 Issue: 2 Pages: 7348-7353

    • DOI

      10.1016/j.ifacol.2023.10.349

    • Peer Reviewed / Open Access / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-23K16998
  • [Presentation] Convolution Method : Model-Less Perfusion Analysis using Back Propagation Method2023

    • Author(s)
      Tomoki Saka
    • Organizer
      IFAC World Congress 2023
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-23K16998

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