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Computer Aided Diagnosis using Big Data Analysis in Medical Imaging

Research Project

Project/Area Number 17K10403
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Research Field Radiation science
Research InstitutionKobe University (2019)
Osaka University (2017-2018)

Principal Investigator

Hori Masatoshi  神戸大学, 医学研究科, 特命教授 (00346206)

Co-Investigator(Kenkyū-buntansha) 大西 裕満  大阪大学, 医学系研究科, 准教授 (20452435)
佐藤 嘉伸  奈良先端科学技術大学院大学, 先端科学技術研究科, 教授 (70243219)
大竹 義人  奈良先端科学技術大学院大学, 先端科学技術研究科, 准教授 (80349563)
Project Period (FY) 2017-04-01 – 2020-03-31
Project Status Completed (Fiscal Year 2019)
Budget Amount *help
¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000)
Fiscal Year 2019: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2018: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Fiscal Year 2017: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Keywords臨床 / 放射線 / コンピュータ支援診断 / ビッグデータ / 画像解析 / CT / MRI / 肝線維化 / 情報工学
Outline of Final Research Achievements

We developed systems that aids the evaluation of medical images (CT, MRI) using the technologies of artificial intelligence and statistical atlas. As applications of these technologies, the following systems were developed: 1) a computerized technique to analyze liver shape and estimate the stage of liver fibrosis, 2) a technique to extract renal arteries from CT images. None of them could immediately obtain clinically applicable accuracy, but the problems for accuracy improvement became clear. Our results show that the techniques are promising for computer aided diagnosis.

Academic Significance and Societal Importance of the Research Achievements

近年、医用画像(CTやMRIなど)のデータ量は増大は著しく、画像診断を支援するコンピュータ・システムへのニーズが増大している。本研究では、人工知能や統計アトラスの技術を開発し、その応用として2種類のシステムを試作して、コンピュータ支援診断の精度向上につながり得る結果を得た。こうしたシステムは、画像診断専門医不足に対応し、多量のデータから医療に有益な情報を精度良く抽出するのに役立つと考えられ、今後の医療レベル向上に貢献することが期待できる。

Report

(4 results)
  • 2019 Annual Research Report   Final Research Report ( PDF )
  • 2018 Research-status Report
  • 2017 Research-status Report
  • Research Products

    (4 results)

All 2019 2017

All Journal Article (1 results) (of which Int'l Joint Research: 1 results,  Peer Reviewed: 1 results) Presentation (3 results)

  • [Journal Article] Liver shape analysis using partial least squares regression-based statistical shape model: application for understanding and staging of liver fibrosis2019

    • Author(s)
      Mazen Soufi, Yoshito Otake, Masatoshi Hori, Kazuya Moriguchi, Yasuharu Imai, Yoshiyuki Sawai, Takashi Ota, Noriyuki Tomiyama, Yoshinobu Sato
    • Journal Title

      International Journal of Computer Assisted Radiology and Surgery

      Volume: 14 Issue: 12 Pages: 2083-2093

    • DOI

      10.1007/s11548-019-02084-z

    • Related Report
      2019 Annual Research Report
    • Peer Reviewed / Int'l Joint Research
  • [Presentation] Deep Learning with Convolutional Neural Network for Automated Segmentation of Renal Arteries: Initial Experience2019

    • Author(s)
      Takashi Ota, Masatoshi Hori, Yuki Suzuki, Hiromitsu Onishi, Atsushi Nakamoto, Yoshito Otake, Yoshinobu Sato, Noriyuki Tomiyama
    • Organizer
      日本医学放射線学会総会
    • Related Report
      2019 Annual Research Report 2018 Research-status Report
  • [Presentation] 形状特徴を用いた肝線維化症の疾患進行度推定2017

    • Author(s)
      森口 和也、大竹 義人、堀 雅敏、岡田 俊之、今井 康陽、大城 幸雄、富山 憲幸、佐藤 嘉伸
    • Organizer
      第36回日本医用画像工学会大会
    • Related Report
      2017 Research-status Report
  • [Presentation] 畳み込みニューラルネットワークを用いた腹部造影CT画像からの微細な腎動脈枝の自動抽出. (Automated segmentation of thin renal artery branches from abdominal CT images using Convolutional Neural Network)2017

    • Author(s)
      小野 真理子、鈴木 裕紀、日朝 祐太、堀 雅敏、富山 憲幸、大竹 義人、佐藤 嘉伸
    • Organizer
      日本コンピュータ外科学会大会
    • Related Report
      2017 Research-status Report

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Published: 2017-04-28   Modified: 2021-02-19  

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