HANAOKA Shouhei 花岡昇平

… Alternative Names

Hanaoka Shouhei 花岡昇平

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Researcher Number	80631382
Other IDs
Affiliation (Current)	2023: 東京大学, 医学部附属病院, 講師
Affiliation (based on the past Project Information) *help	2020 – 2021: 東京大学, 医学部附属病院, 講師 2018 – 2019: 東京大学, 医学部附属病院, 助教 2017: 東京大学, 医学部附属病院, 特任講師 2015 – 2016: 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 Basic Section 90130:Medical systems-related / Science and Engineering / Radiation science / Medical systems
Keywords	Principal Investigator X線CT / 医用画像処理 / 深層学習 / 異常検知 / 医用画像工学 / 骨疾患 / MRI / 計算解剖学 / コンピュータ支援診断 / 骨転移 … More / コンピュータ支援検出 / 放射線診断学 / 架空画像生成 / 肺癌 / 胸部単純写真 / ディープラーニング / 時間差分 / 画像 / 解剖学 / 放射線 / 教師なし学習 / PET / 解剖学的ランドマーク / 多元計算解剖学 / セグメンテーション / 転移性骨腫瘍 / 悪性腫瘍骨転移 / 医用画像解析 / 悪性腫瘍 / コンピュータ支援画像診断 / 画像診断システム Less

Research Projects
(6 results)
Research Products
(23 results)

Automatic creation of a large amount of virtual normal and abnormal medical imagesPrincipal Investigator
- Principal Investigator
  
  花岡昇平
- Project Period (FY)
  2021 – 2023
- 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 bony lesion detection system for CT images by unsupervised deep learningPrincipal Investigator
- Principal Investigator
  
  Hanaoka Shouhei
- 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 Investigator
- 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
development of bony lesion detection system for CT images and its clinical applicationPrincipal Investigator
- Principal Investigator
  
  Hanaoka Shouhei
- 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 2022 2021 2019 2018 2017 2016 2014 2013 2012

All Journal Article Presentation

[Journal Article] Unsupervised Deep Anomaly Detection in Chest Radiographs2021
- Author(s)
  Nakao Takahiro、Hanaoka Shouhei、Nomura Yukihiro、Murata Masaki、Takenaga Tomomi、Miki Soichiro、Watadani Takeyuki、Yoshikawa Takeharu、Hayashi Naoto、Abe Osamu
- Journal Title
  
  Journal of Digital Imaging
  
  Volume: n/a Issue: 2 Pages: 418-427
- DOI
  10.1007/s10278-020-00413-2
- Peer Reviewed / Open Access
- Data Source
  KAKENHI-PROJECT-18K12095, KAKENHI-PROJECT-18K12096
[Journal Article] Clinical usefulness of temporal subtraction CT in detecting vertebral bone metastases2019
- Author(s)
  Hoshiai Sodai、Masumoto Tomohiko、Hanaoka Shouhei、Nomura Yukihiro、Mori Kensaku、Hara Tadashi、Saida Tsukasa、Okamoto Yoshikazu、Minami Manabu
- Journal Title
  
  European Journal of Radiology
  
  Volume: 118 Pages: 175-180
- DOI
  10.1016/j.ejrad.2019.07.024
- Peer Reviewed
- Data Source
  KAKENHI-PROJECT-18K12095
[Journal Article] HoTPiG: a novel graph-based 3-D image feature set and its applications to computer-assisted detection of cerebral aneurysms and lung nodules2019
- Author(s)
  Hanaoka Shouhei、Nomura Yukihiro、Takenaga Tomomi、Murata Masaki、Nakao Takahiro、Miki Soichiro、Yoshikawa Takeharu、Hayashi Naoto、Abe Osamu、Shimizu Akinobu
- Journal Title
  
  International Journal of Computer Assisted Radiology and Surgery
  
  Volume: epub ahead Issue: 12 Pages: 2095-2107
- DOI
  10.1007/s11548-019-01942-0
- Peer Reviewed
- Data Source
  KAKENHI-PROJECT-18K12095, KAKENHI-PUBLICLY-17H05282, KAKENHI-PLANNED-26108002
[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
  
  International Journal of Computer Assisted Radiology and Surgery
  
  Volume: 12(3) Issue: 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
[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
  
  International Journal of Computer Assisted Radiology and Surgery
  
  Volume: 印刷中 Issue: 5 Pages: 719-732
- DOI
  10.1007/s11548-016-1516-y
- Peer Reviewed / Acknowledgement Compliant
- Data Source
  KAKENHI-PUBLICLY-15H01108, KAKENHI-ORGANIZER-26108001, KAKENHI-PROJECT-15K19775, KAKENHI-PLANNED-26108002
[Presentation] Artificial chest X-ray image creation with simulated lung nodules by Glow algorithm2022
- Author(s)
  Hanaoka S., Nomura Y., Hayashi N., Shibata H., Nakao T., Takenaga T., Abe O.
- Organizer
  Computer Assisted Radiology and Surgery (CARS) 2022
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-21K12722
[Presentation] Development of temporal subtraction CT images using deep learning to detect vertebral bone metastases2021
- Author(s)
  星合壮大、花岡昇平、野村行弘、他
- Organizer
  第80回日本医学放射線学会総会
- Data Source
  KAKENHI-PROJECT-18K12095
[Presentation] Residual network-based unsupervised temporal image subtraction for highlighting bone metastases2018
- Author(s)
  Shouhei Hanaoka
- Organizer
  CARS 2018, Berlin, 18th May, 2018
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-18K12095
[Presentation] 胸部FDG-PETCT画像におけるdeep learningを用いた異常検知2018
- Author(s)
  花岡昇平
- Organizer
  第1回日本医用画像人工知能研究会学術集会
- Data Source
  KAKENHI-PUBLICLY-17H05282
[Presentation] A primitive study on unsupervised anomaly detection with an autoencoder in emergency head CT volumes2018
- Author(s)
  Sato D, Hanaoka S, Nomura Y, Takenaga T, Miki S, Yoshikawa T, Hayashi N, Abe O
- Organizer
  SPIE Medical Imaging 2018, Houston, TX, USA, February 11-15, 2018
- Int'l Joint Research
- Data Source
  KAKENHI-PUBLICLY-17H05282
[Presentation] Residual network-based unsupervised temporal image subtraction for highlighting bone metastases2018
- Author(s)
  S. Hanaoka, T. Masumoto, S. Hoshiai, Y. Nomura, T. Takenaga, M. Murata, S. Miki, T. Yoshikawa, N. Hayashi, O. Abe
- Organizer
  CARS 2018 Computer Assisted Radiology and Surgery. June 20 - 23, 2018, Hotel NH Collection Friedrichstrasse, Berlin, Germany
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-15K19775
[Presentation] Residual network-based unsupervised temporal image subtraction for highlighting bone metastases2018
- Author(s)
  Shouhei Hanaoka
- Organizer
  CARS 2018, Berlin, 18th May, 2018
- Int'l Joint Research
- Data Source
  KAKENHI-PUBLICLY-17H05282
[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
  2016-06-21
- 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] 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] 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] 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

HANAOKA Shouhei 花岡 昇平

Hanaoka Shouhei 花岡 昇平

Research Projects

Research Products

Automatic creation of a large amount of virtual normal and abnormal medical imagesPrincipal Investigator

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

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

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

Development of local appearance model of normal organs by DCNNPrincipal Investigator

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

development of bony lesion detection system for CT images and its clinical applicationPrincipal Investigator

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] Unsupervised Deep Anomaly Detection in Chest Radiographs2021

Author(s)

Journal Title

DOI

Data Source

[Journal Article] Clinical usefulness of temporal subtraction CT in detecting vertebral bone metastases2019

Author(s)

Journal Title

DOI

Data Source

[Journal Article] HoTPiG: a novel graph-based 3-D image feature set and its applications to computer-assisted detection of cerebral aneurysms and lung nodules2019

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

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

Author(s)

Journal Title

DOI

Data Source

[Presentation] Artificial chest X-ray image creation with simulated lung nodules by Glow algorithm2022

Author(s)

Organizer

Data Source

[Presentation] Development of temporal subtraction CT images using deep learning to detect vertebral bone metastases2021

Author(s)

Organizer

Data Source

[Presentation] Residual network-based unsupervised temporal image subtraction for highlighting bone metastases2018

Author(s)

Organizer

Data Source

[Presentation] 胸部FDG-PETCT画像におけるdeep learningを用いた異常検知2018

Author(s)

Organizer

HANAOKA Shouhei 花岡昇平

Hanaoka Shouhei 花岡昇平