Yoshikawa Takeharu 吉川健啓

Researcher Number	30293476
Other IDs	https://orcid.org/0000-0002-4096-7908
Affiliation (Current)	2024: 東京大学, 医学部附属病院, 特任教授
Affiliation (based on the past Project Information) *help	2020 – 2022: 東京大学, 医学部附属病院, 特任准教授
Review Section/Research Field	Principal Investigator Basic Section 52040:Radiological sciences-related
Keywords	Principal Investigator MRI / 肺 / 胸水 / AI / CAD / 検診 / スクリーニング / 肺がん / 肺MRI

Feasibility study of lung nodule screening using pulmonary MRI and development of computer-assisted detection softwarePrincipal Investigator
- Principal Investigator
  
  Yoshikawa Takeharu
- Project Period (FY)
  2020 – 2022
- Research Category
  
  Grant-in-Aid for Scientific Research (C)
- Review Section
  
  Basic Section 52040:Radiological sciences-related
- Research Institution
  The University of Tokyo

All 2023 2021 2020

All Presentation

[Presentation] Automated segmentation of lung area and bronchi regions in ultra-short TE MR images using deep learning2023
- Author(s)
  Takahashi M, Nomura Y, Takenaga T, Hanaoka S, Yoshikawa T, Abe S
- Organizer
  第79回放射線技術学会総会学術大会
- Data Source
  KAKENHI-PROJECT-20K08045
[Presentation] The prevalence and clinical significance of pleural fluid detected by chest MRI: a cross-sectional study in a medical checkup setting2021
- Author(s)
  Fukuda K, Matsuzaki H, Saito A, Nagase T, Yoshikawa T
- Organizer
  The 25th Congress of the Asian Pacific Society of Respirology
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-20K08045
[Presentation] Feasibility study of nodule conspicuity for lung screening using ultrashort echo time MRI2020
- Author(s)
  Koshino S, Yoshikawa T, Nomura Y, Miki S, Hanaoka S, Watadani T, Hayashi N, Abe O
- Organizer
  2020 ISMRM & SMRT VIRTUAL CONFERENCE & EXHIBITION
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-20K08045

1. 越野沙織 (50801552)

# of Collaborated Projects: 1 results

# of Collaborated Products: 1 results

Yoshikawa Takeharu 吉川健啓

Research Projects

Research Products

Co-Researchers

Feasibility study of lung nodule screening using pulmonary MRI and development of computer-assisted detection softwarePrincipal Investigator

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

[Presentation] Automated segmentation of lung area and bronchi regions in ultra-short TE MR images using deep learning2023

Author(s)

Organizer

Data Source

[Presentation] The prevalence and clinical significance of pleural fluid detected by chest MRI: a cross-sectional study in a medical checkup setting2021

Author(s)

Organizer

Data Source

[Presentation] Feasibility study of nodule conspicuity for lung screening using ultrashort echo time MRI2020

Author(s)

Organizer

Data Source

Yoshikawa Takeharu 吉川 健啓

Research Projects

Research Products

Co-Researchers

Feasibility study of lung nodule screening using pulmonary MRI and development of computer-assisted detection softwarePrincipal Investigator

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

[Presentation] Automated segmentation of lung area and bronchi regions in ultra-short TE MR images using deep learning2023

Author(s)

Organizer

Data Source

[Presentation] The prevalence and clinical significance of pleural fluid detected by chest MRI: a cross-sectional study in a medical checkup setting2021

Author(s)

Organizer

Data Source

[Presentation] Feasibility study of nodule conspicuity for lung screening using ultrashort echo time MRI2020

Author(s)

Organizer

Data Source

Yoshikawa Takeharu 吉川健啓