Yamamoto Megumi 山本めぐみ

Researcher Number	50412333
Other IDs
Affiliation (Current)	2022: 広島国際大学, 保健医療学部, 講師
Affiliation (based on the past Project Information) *help	2014 – 2020: 広島国際大学, 保健医療学部, 助教
Review Section/Research Field	Principal Investigator Medical Physics and Radiological Technology / Radiation science / Basic Section 52040:Radiological sciences-related
Keywords	Principal Investigator DSA / アーチファクト / 医用画像処理 / 放射線科学 / 血管造影 / 深層学習 / 冠動脈造影 / 機械学習 / 循環器 / 画像処理工学 … More / 冠動脈 / 造影 / Deep Learning / モーションアーチファクト / ニューラルネットワーク / 人工知能 / アンギオ / 血管 / 情報工学 / 敵対的生成ネットワーク / Deep　Learning Less

敵対的生成ネットワークを用いた新しい原理にもとづくDSAの開発Principal Investigator
- Principal Investigator
  
  山本めぐみ
- Project Period (FY)
  2020 – 2023
- Research Category
  
  Grant-in-Aid for Scientific Research (C)
- Review Section
  
  Basic Section 52040:Radiological sciences-related
- Research Institution
  Hiroshima International University
Development of 3D-DSA using by Deep LearningPrincipal Investigator
- Principal Investigator
  
  山本めぐみ
- Project Period (FY)
  2017 – 2021
- Research Category
  
  Grant-in-Aid for Young Scientists (B)
- Research Field
  
  Medical Physics and Radiological Technology
  Radiation science
- Research Institution
  Hiroshima International University
Development of super high resolution DSA for coronary arteryPrincipal Investigator
- Principal Investigator
  
  Yamamoto Megumi
- Project Period (FY)
  2014 – 2016
- Research Category
  
  Grant-in-Aid for Young Scientists (B)
- Research Field
  
  Medical Physics and Radiological Technology
- Research Institution
  Hiroshima International University

All 2019 2018 2017 2016 2015

All Journal Article Presentation Patent

[Journal Article] A new method for reducing large motion artifacts of DSA based on deep learning technique2019
- Author(s)
  M.Yamamoto, Y.Okura, H.kawata, N.Yamamoto
- Journal Title
  
  Journal of the International Foundation for Computer Assisted Radiology and Surgery
  
  Volume: volume14/spplement1
- Data Source
  KAKENHI-PROJECT-17K18291
[Journal Article] 対向データを利用した補間法によるSPECT再構成法の開発2017
- Author(s)
  山口雄貴　大倉保彦　山本めぐみ
- Journal Title
  
  第36回日本医用画像工学会大会
  
  Volume: ー Pages: 365-371
- Data Source
  KAKENHI-PROJECT-17K18291
[Journal Article] 機械学習を用いた冠動脈DSAに関する研究2017
- Author(s)
  山本めぐみ　大倉保彦
- Journal Title
  
  第36回日本医用画像工学会大会
  
  Volume: ー Pages: 249-252
- Data Source
  KAKENHI-PROJECT-17K18291
[Journal Article] A method for reducing motion artifacts of DSA using deep learning technique2017
- Author(s)
  Megumi Yamamoto, Yasuhiko Okura
- Journal Title
  
  医学物理
  
  Volume: 37, sup3 Pages: 184-184
- Data Source
  KAKENHI-PROJECT-17K18291
[Journal Article] To investigate the effect of machine learning for Coronary DSA2016
- Author(s)
  Yamamoto.M、Okura.Y
- Journal Title
  
  医学物理学会
  
  Volume: 36 Pages: 197-197
- Acknowledgement Compliant
- Data Source
  KAKENHI-PROJECT-26860408
[Journal Article] A New Digital Subtraction Angiography For Coronary Artery By Using Density Difference Dependent Mask Image2015
- Author(s)
  M. Yamamoto, Y.Okura
- Journal Title
  
  Int J CARS(2015) 10(Suppl 1)
  
  Volume: 10 Pages: 9-10
- Data Source
  KAKENHI-PROJECT-26860408
[Patent] 生体画像処理装置、出力画像製造方法、学習結果製造方法、及びプログラム2016
- Inventor(s)
  山本めぐみ、大倉保彦
- Industrial Property Rights Holder
  学校法人常翔学園
- Industrial Property Rights Type
  特許
- Filing Date
  2016-12-07
- Data Source
  KAKENHI-PROJECT-26860408
[Presentation] A new method for reducing large motion artifacts of DSA based on deep learning technique2019
- Author(s)
  M.Yamamoto, Y.Okura, H.kawata, N.Yamamoto
- Organizer
  International Journal of Computer Assisted Radiology and Surgery
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-17K18291
[Presentation] A method for reducing large motion artifacts of DSA based on deep learning technique2019
- Author(s)
  山本めぐみ,大倉保彦,川田秀道, 山本直樹
- Organizer
  日本放射線技術学会第75回総会学術大会
- Data Source
  KAKENHI-PROJECT-17K18291
[Presentation] Development of a new method to reduce large motion artifacts for DSA used by Deep Learning2018
- Author(s)
  Megumi Yamamoto
- Organizer
  IUPESM2018-World Congress on Medical Physics & Biomedical Engineering
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-17K18291
[Presentation] A method for reducing motion artifacts of DSA using deep learning technique2017
- Author(s)
  Megumi Yamamoto, Yasuhiko Okura
- Organizer
  114th Scientific Meeting of JSMP
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-17K18291
[Presentation] Digital subtraction angiography for coronary artery using deep learning technique2017
- Author(s)
  山本めぐみ
- Organizer
  European Congress of Radiology
- Place of Presentation
  ウィーンコンベンションセンター
- Year and Date
  2017-03-01
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-26860408
[Presentation] Development of a New Digital Subtraction Angiography Technique for Coronary Artery via Machine Learning2017
- Author(s)
  Megumi Yamamoto, Yasuhiko Okura
- Organizer
  第73回日本放射線技術学会総会学術大会
- Data Source
  KAKENHI-PROJECT-17K18291
[Presentation] 機械学習を用いた冠動脈DSAに関する研究2017
- Author(s)
  山本めぐみ, 大倉保彦
- Organizer
  第36回日本医用画像工学会
- Data Source
  KAKENHI-PROJECT-17K18291
[Presentation] Development of a New Digita Subtraction Angiography Technique for coronary Artery via Machine Learning2017
- Author(s)
  山本めぐみ
- Organizer
  日本放射線技術学会
- Place of Presentation
  パシフィコ横浜
- Year and Date
  2017-04-14
- Data Source
  KAKENHI-PROJECT-26860408
[Presentation] DSAへの深層学習の応用2017
- Author(s)
  山本めぐみ
- Organizer
  第45回日本放射線技術学会秋季学術大会
- Data Source
  KAKENHI-PROJECT-17K18291
[Presentation] 対向データを利用した補間法によるSPECT再構成法の開発2017
- Author(s)
  山口雄貴, 大倉保彦, 山本めぐみ
- Organizer
  第36回日本医用画像工学会
- Data Source
  KAKENHI-PROJECT-17K18291
[Presentation] 機械学習を用いた冠動脈DSA法に関する研究2016
- Author(s)
  山本めぐみ
- Organizer
  医用画像情報学会
- Place of Presentation
  大阪市立大学
- Year and Date
  2016-06-11
- Data Source
  KAKENHI-PROJECT-26860408
[Presentation] To investigate the effective of machine learning for coronary DSA2016
- Author(s)
  山本めぐみ
- Organizer
  医学物理学会
- Place of Presentation
  沖縄コンベンションセンター
- Year and Date
  2016-09-09
- Data Source
  KAKENHI-PROJECT-26860408
[Presentation] Development of digital subtraction angiography for coronary artery without motion artifacts enabling read-time processing2015
- Author(s)
  山本めぐみ
- Organizer
  IUPESM World Congress On Medical Physics & Biomedical Engineering 2015(世界医学物理生体医工学会)
- Place of Presentation
  カナダ(トロント)
- Year and Date
  2015-06-07
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-26860408
[Presentation] A New Digital Subtraction Angiography For Coronary Artery By Using Density Difference Dependent Mask Image2015
- Author(s)
  山本めぐみ
- Organizer
  Computer Assisted Radiology and Surgery 2015(第29回国際コンピュータ支援放射線医学・外科学会議)
- Place of Presentation
  スペイン(バルセロナ)
- Year and Date
  2015-06-24
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-26860408

1. 大倉保彦 (80369769)

# of Collaborated Projects: 1 results

# of Collaborated Products: 0 results

Yamamoto Megumi 山本 めぐみ

Research Projects

Research Products

Co-Researchers

敵対的生成ネットワークを用いた新しい原理にもとづくDSAの開発Principal Investigator

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

Development of 3D-DSA using by Deep LearningPrincipal Investigator

Principal Investigator

Project Period (FY)

Research Category

Research Field

Research Institution

Development of super high resolution DSA for coronary arteryPrincipal Investigator

Principal Investigator

Project Period (FY)

Research Category

Research Field

Research Institution

[Journal Article] A new method for reducing large motion artifacts of DSA based on deep learning technique2019

Author(s)

Journal Title

Data Source

[Journal Article] 対向データを利用した補間法によるSPECT再構成法の開発2017

Author(s)

Journal Title

Data Source

[Journal Article] 機械学習を用いた冠動脈DSAに関する研究2017

Author(s)

Journal Title

Data Source

[Journal Article] A method for reducing motion artifacts of DSA using deep learning technique2017

Author(s)

Journal Title

Data Source

[Journal Article] To investigate the effect of machine learning for Coronary DSA2016

Author(s)

Journal Title

Data Source

[Journal Article] A New Digital Subtraction Angiography For Coronary Artery By Using Density Difference Dependent Mask Image2015

Author(s)

Journal Title

Data Source

[Patent] 生体画像処理装置、出力画像製造方法、学習結果製造方法、及びプログラム2016

Inventor(s)

Industrial Property Rights Holder

Industrial Property Rights Type

Filing Date

Data Source

[Presentation] A new method for reducing large motion artifacts of DSA based on deep learning technique2019

Author(s)

Organizer

Data Source

[Presentation] A method for reducing large motion artifacts of DSA based on deep learning technique2019

Author(s)

Organizer

Data Source

[Presentation] Development of a new method to reduce large motion artifacts for DSA used by Deep Learning2018

Author(s)

Organizer

Data Source

[Presentation] A method for reducing motion artifacts of DSA using deep learning technique2017

Author(s)

Organizer

Data Source

[Presentation] Digital subtraction angiography for coronary artery using deep learning technique2017

Author(s)

Organizer

Place of Presentation

Year and Date

Data Source

[Presentation] Development of a New Digital Subtraction Angiography Technique for Coronary Artery via Machine Learning2017

Author(s)

Organizer

Data Source

[Presentation] 機械学習を用いた冠動脈DSAに関する研究2017

Author(s)

Yamamoto Megumi 山本めぐみ