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In silico disease classification based on brain perfusion SPECT

Research Project

Project/Area Number 25870406
Research Category

Grant-in-Aid for Young Scientists (B)

Allocation TypeMulti-year Fund
Research Field Physical pharmacy
Intelligent informatics
Research InstitutionHokuriku University (2015-2016)
Osaka University (2013-2014)

Principal Investigator

OKAMOTO Kousuke  北陸大学, 薬学部, 講師 (70437309)

Project Period (FY) 2013-04-01 – 2017-03-31
Project Status Completed (Fiscal Year 2016)
Budget Amount *help
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2015: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2014: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2013: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
Keywords画像の識別 / データマイニング / 画像診断 / 知識の発見
Outline of Final Research Achievements

Brain perfusion SPECT is an imaging technique to evaluate a cerebral blood flow (CBF) in diagnosis of several neurodegenerative diseases. In this study, our aims are to build the model which enables us to classify some neurodegenerative diseases based on SPECT images, and to supply the information about the brain regions that it is important for the prediction of the diseases.
We built the model to classify three kinds of diseases (Alzheimer disease, Parkinson disease or other neurodegenerative diseases) by support vector machine. In the prediction, brain regions whose CBF was different between the diseases and which were included into the SVM model were not conflict with clinical knowledge. Therefore, the model and information about the brain regions obtained in this study should be useful for computer aided diagnosis.

Report

(5 results)
  • 2016 Annual Research Report   Final Research Report ( PDF )
  • 2015 Research-status Report
  • 2014 Research-status Report
  • 2013 Research-status Report
  • Research Products

    (4 results)

All 2015 2014

All Presentation (4 results)

  • [Presentation] SPECT脳血流画像に基づく機械学習を用いた疾患判別予測モデルの構築2015

    • Author(s)
      阪本健也, 幡生あすか, 高木達也, 岡本晃典
    • Organizer
      第55回日本核医学会学術総会
    • Place of Presentation
      東京
    • Year and Date
      2015-11-05
    • Related Report
      2015 Research-status Report
  • [Presentation] 脳血流画像に基づく機械学習を用いた疾患予測モデルの検討2015

    • Author(s)
      幡生あすか
    • Organizer
      生命医薬情報学連合大会2015年大会
    • Place of Presentation
      京都
    • Year and Date
      2015-10-29
    • Related Report
      2015 Research-status Report
  • [Presentation] SPECT脳血流画像に基づく機械学習を用いた疾患判別予測モデルの構築2015

    • Author(s)
      阪本健也、幡生あすか、高木達也、岡本晃典、川下理日人
    • Organizer
      日本薬学会第135年会
    • Place of Presentation
      神戸
    • Year and Date
      2015-03-27
    • Related Report
      2014 Research-status Report
  • [Presentation] SPECT脳血流画像に基づく機械学習を用いた疾患判別2014

    • Author(s)
      阪本健也, 幡生あすか, 岡本晃典, 川下理日, 高木達也
    • Organizer
      日本薬学会第134年会
    • Place of Presentation
      熊本市総合体育館(熊本県)
    • Related Report
      2013 Research-status Report

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Published: 2014-07-25   Modified: 2019-07-29  

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