HANAOKA Shouhei 花岡昇平

Researcher Number	80631382
Affiliation *help	2015 – 2018 : 東京大学, 医学部附属病院, 助教 2012 – 2013 : 東京大学, 医学部附属病院, 助教
Review Section/Research Field	Principal Investigator Science and Engineering / Radiation science / Basic Section 90130:Medical systems-related / Medical systems
Keywords	Principal Investigator 医用画像処理 / X線CT / 異常検知 / 医用画像工学 / 放射線診断学 / 計算解剖学 / 骨疾患 / 解剖学的ランドマーク / 放射線 / ディープラーニング … More

development of bony lesion detection system for CT images by unsupervised deep learningPrincipal InvestigatorOngoing
- Principal Investigator
  
  花岡昇平
- Project Period (FY)
  2018 – 2020
- Research Category
  
  Grant-in-Aid for Scientific Research (C)
- Review Section
  
  Basic Section 90130:Medical systems-related
- Research Institution
  The University of Tokyo
Development of local appearance model of normal organs by DCNNPrincipal InvestigatorOngoing
- Principal Investigator
  
  花岡昇平
- Project Period (FY)
  2017 – 2018
- Research Category
  
  Grant-in-Aid for Scientific Research on Innovative Areas (Research in a proposed research area)
- Review Section
  
  Science and Engineering
- Research Institution
  The University of Tokyo
X線CT画像における骨転移の自動診断システムの開発および初期臨床応用Principal InvestigatorOngoing
- Principal Investigator
  
  花岡昇平
- Project Period (FY)
  2015 – 2017
- Research Category
  
  Grant-in-Aid for Young Scientists (B)
- Research Field
  
  Radiation science
- Research Institution
  The University of Tokyo
多様な画像データベースからの解剖学的ランドマーク点自動定義アルゴリズムの開発Principal Investigator
- Principal Investigator
  
  花岡昇平
- Project Period (FY)
  2015 – 2016
- Research Category
  
  Grant-in-Aid for Scientific Research on Innovative Areas (Research in a proposed research area)
- Review Section
  
  Science and Engineering
- Research Institution
  The University of Tokyo
Development of automatic detection application for bone metastases in X-ray CT imagesPrincipal Investigator
- Principal Investigator
  
  HANAOKA Shouhei
- Project Period (FY)
  2012 – 2013
- Research Category
  
  Grant-in-Aid for Research Activity start-up
- Research Field
  
  Medical systems
- Research Institution
  The University of Tokyo

All 2017 2016 2014 2013 2012

All Journal Article Presentation

[Journal Article] Automatic detection of vertebral number abnormalities in body CT images2017
- Author(s)
  Hanaoka S, Nakano Y, Nemoto M, Nomura Y, Takenaga T, Miki S, Yoshikawa T, Hayashi N, Masutani Y, Shimizu A
- Journal Title
  
  Int J Comput Assist Radiol Surg
  
  Volume : 印刷中
- DOI
  10.1007/s11548-016-1516-y
- Peer Reviewed / Acknowledgement Compliant
- Data Source
  KAKENHI-PUBLICLY-15H01108, KAKENHI-ORGANIZER-26108001, KAKENHI-PROJECT-15K19775
[Journal Article] Landmark-guided diffeomorphic demons algorithm and its application to automatic segmentation of the whole spine and pelvis in CT images2017
- Author(s)
  Hanaoka S, Masutani Y, Nemoto M, Nomura Y, Miki S, Yoshikawa T, Hayashi N, Ohtomo K, Shimizu A.
- Journal Title
  
  Int J Comput Assist Radiol Surg
  
  Volume : 12(3) Pages : 413-430
- DOI
  10.1007/s11548-016-1507-z
- Peer Reviewed / Acknowledgement Compliant
- Data Source
  KAKENHI-PUBLICLY-15H01108, KAKENHI-ORGANIZER-26108001, KAKENHI-PLANNED-26108002, KAKENHI-PROJECT-15K19775, KAKENHI-INTERNATIONAL-15K21716
[Presentation] Fully automatic definition of anatomical landmarks in medical images: a feasibility study2016
- Author(s)
  Shouhei Hanaoka, Yukihiro Nomura, Mitsutaka Nemoto, et al.
- Organizer
  CARS (computer assisted radiology and surgery) 2016, Heidelberg, Germany
- Place of Presentation
  Heidelberg, Germany
- Year and Date
  2016-06-21
- Int'l Joint Research
- Data Source
  KAKENHI-PUBLICLY-15H01108
[Presentation] Fully automatic definition of anatomical landmarks in medical images: a feasibility study2016
- Author(s)
  Shouhei Hanaoka, Yukihiro Nomura, Mitsutaka Nemoto, et al.
- Organizer
  CARS (computer assisted radiology and surgery) 2016
- Place of Presentation
  Heidelberg, Germany
- Year and Date
  2016-06-21
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-15K19775
[Presentation] Fully automatic definition of anatomical landmarks in medical images: a feasibility study2016
- Author(s)
  Hanaoka S, Nomura Y, Nemoto M, Miki S, Yoshikawa T, Hayashi N, Ohtomo K, Shimizu A
- Organizer
  Computer assisted radiology and surgery 2016
- Place of Presentation
  Heidelberg, Germany
- Year and Date
  2016-06-22
- Int'l Joint Research
- Data Source
  KAKENHI-PUBLICLY-15H01108
[Presentation] Fully automatic definition of anatomical landmarks in medical images: a feasibility study2016
- Author(s)
  Hanaoka S, Nomura Y, Nemoto M, Miki S, Yoshikawa T, Hayashi N, Ohtomo K, Shimizu A
- Organizer
  Computer Assisted Radiology and Surgery 2016
- Place of Presentation
  Heidelberg, Germany
- Year and Date
  2016-06-21
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-15K19775
[Presentation] Semiautomatic segmentation of whole-spinal vertebrae in CT volumes by multi-atlas method: accuracy improvement by using anatomical landmark position information2014
- Author(s)
  Shouhei Hanaoka, Mitsutaka Nemoto, Yukihiro Nomura, Soichiro Miki, Takeharu Yoshikawa, Naoto Hayashi, Kuni Ohtomo, Yoshitaka Masutani
- Organizer
  Computer assisted radiology and surgery 2014
- Place of Presentation
  福岡コンベンションセンター
- Data Source
  KAKENHI-PROJECT-24800017
[Presentation] Automated detection of anomalous spinal segmenta- tions : A feasibility study by using 300 CT datasets2014
- Author(s)
  Y Nakano, S Hanaoka, M Nemoto, Y Masutani, N Hayashi, and K Ohtomo
- Organizer
  The 73rd annual meeting of the Japan Radiological Society
- Place of Presentation
  Yokohama, Japan
- Year and Date
  2014-04-12
- Data Source
  KAKENHI-PROJECT-24800017
[Presentation] Semiautomatic segmentation of whole-spinal vertebrae in CT volumes by multi-atlas method : accuracy improvement by using anatomical landmark position information2014
- Author(s)
  S Hanaoka, Y Masutani, M Nemoto, Y Nomura, S Miki, T Yoshikawa, N Hayashi, and K Ohtomo
- Organizer
  Computer assisted radiol- ogy and surgery
- Place of Presentation
  Fukuoka, Japan (accepted)
- Year and Date
  2014-06-27
- Data Source
  KAKENHI-PROJECT-24800017
[Presentation] Sparse Gaussian graphical model of spatial distribution of ana- tomical landmarks–whole torso model building with training datasets of partial imaging ranges2013
- Author(s)
  S Hanaoka, Y Masutani, M Nemoto, Y Nomura, S Miki, T Yoshikawa, N Hayashi, and K Ohtomo
- Organizer
  Fourth MICAI workshop on Mathematical Founadtions of Computational Anatomy (MFCA)
- Place of Presentation
  Nagoya, Japan
- Year and Date
  2013-09-22
- Data Source
  KAKENHI-PROJECT-24800017
[Presentation] A multiple anatomical landmark detection system for body CT images2013
- Author(s)
  S Hanaoka, M Nemoto, Y Nomura, S Miki, Yoshikawa, N Hayashi, K Ohtomo, and Y Masutani
- Organizer
  First International Workshop on Bioimage Recognition (BIR)
- Place of Presentation
  Matsuyama, Japan
- Year and Date
  2013-12-05
- Data Source
  KAKENHI-PROJECT-24800017
[Presentation] A multiple anatomical landmark detection system for body CT images2013
- Author(s)
  Shouhei Hanaoka, Mitsutaka Nemoto, Yukihiro Nomura, Soichiro Miki, Takeharu Yoshikawa, Naoto Hayashi, Kuni Ohtomo, Yoshitaka Masutani
- Organizer
  1st International Workshop on BioImage Recognition
- Place of Presentation
  松山市ひめぎんホール
- Data Source
  KAKENHI-PROJECT-24800017
[Presentation] Automatic categorization of anatomical landmark-local appearances based on diffeomorphic emons and spectral clustering for constructing detector ensembles2012
- Author(s)
  Shouhei Hanaoka
- Organizer
  International conference on medical image computing and computer assited intervention (MICCAI) 2012, Octover 2012, Nice, France
- Place of Presentation
  Nice, France
- Data Source
  KAKENHI-PROJECT-24800017

1. 清水昭伸

# of Collaborated Projects : 0results

# of Collaborated Products : 2results
2. 増谷佳孝

# of Collaborated Projects : 0results

# of Collaborated Products : 2results

HANAOKA Shouhei 花岡 昇平

Research Projects

Research Products

Co-Researchers

development of bony lesion detection system for CT images by unsupervised deep learningPrincipal InvestigatorOngoing

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

Development of local appearance model of normal organs by DCNNPrincipal InvestigatorOngoing

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

X線CT画像における骨転移の自動診断システムの開発および初期臨床応用Principal InvestigatorOngoing

Principal Investigator

Project Period (FY)

Research Category

Research Field

Research Institution

多様な画像データベースからの解剖学的ランドマーク点自動定義アルゴリズムの開発Principal Investigator

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

Development of automatic detection application for bone metastases in X-ray CT imagesPrincipal Investigator

Principal Investigator

Project Period (FY)

Research Category

Research Field

Research Institution

[Journal Article] Automatic detection of vertebral number abnormalities in body CT images2017

Author(s)

Journal Title

DOI

Data Source

[Journal Article] Landmark-guided diffeomorphic demons algorithm and its application to automatic segmentation of the whole spine and pelvis in CT images2017

Author(s)

Journal Title

DOI

Data Source

[Presentation] Fully automatic definition of anatomical landmarks in medical images: a feasibility study2016

Author(s)

Organizer

Place of Presentation

Year and Date

Data Source

[Presentation] Fully automatic definition of anatomical landmarks in medical images: a feasibility study2016

Author(s)

Organizer

Place of Presentation

Year and Date

Data Source

[Presentation] Fully automatic definition of anatomical landmarks in medical images: a feasibility study2016

Author(s)

Organizer

Place of Presentation

Year and Date

Data Source

[Presentation] Fully automatic definition of anatomical landmarks in medical images: a feasibility study2016

Author(s)

Organizer

Place of Presentation

Year and Date

Data Source

[Presentation] Semiautomatic segmentation of whole-spinal vertebrae in CT volumes by multi-atlas method: accuracy improvement by using anatomical landmark position information2014

Author(s)

Organizer

Place of Presentation

Data Source

[Presentation] Automated detection of anomalous spinal segmenta- tions : A feasibility study by using 300 CT datasets2014

Author(s)

Organizer

Place of Presentation

Year and Date

Data Source

[Presentation] Semiautomatic segmentation of whole-spinal vertebrae in CT volumes by multi-atlas method : accuracy improvement by using anatomical landmark position information2014

HANAOKA Shouhei 花岡昇平