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HANAOKA Shouhei  花岡 昇平

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Hanaoka Shouhei  花岡 昇平

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Researcher Number 80631382
Other IDs
Affiliation (Current) 2025: 東京大学, 医学部附属病院, 准教授
Affiliation (based on the past Project Information) *help 2025: 東京大学, 医学部附属病院, 准教授
2024: 東京大学, 医学部附属病院, 講師
2023: 東京大学, 医学部附属病院, 准教授
2022: 東京大学, 医学部附属病院, 専任講師
2020 – 2021: 東京大学, 医学部附属病院, 講師 … More
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 Less
Review Section/Research Field
Principal Investigator
Basic Section 90130:Medical systems-related / Science and Engineering / Sections That Are Subject to Joint Review: Basic Section90130:Medical systems-related , Basic Section90140:Medical technology assessment-related / Basic Section 90140:Medical technology assessment-related / Radiation science / Medical systems
Except Principal Investigator
Basic Section 52040:Radiological sciences-related
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 / 医用画像AI / 人工病変埋め込み / 架空病変生成 / 架空画像生成 / 病変検出AI / 肺癌 / 胸部単純写真 / 架空病変作成 / 架空画像作成 / 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 … More
Except Principal Investigator
Oncology / Deep-learning / Frailty / Computed tomography / Sarcopenia Less
  • Research Projects

    (8 results)
  • Research Products

    (25 results)
  • Co-Researchers

    (4 People)
  •  全ての放射線科医用画像を解釈する基盤モデルの開発Principal Investigator

    • Principal Investigator
      花岡 昇平
    • Project Period (FY)
      2025 – 2028
    • Research Category
      Grant-in-Aid for Scientific Research (B)
    • Review Section
      Basic Section 90130:Medical systems-related
      Basic Section 90140:Medical technology assessment-related
      Sections That Are Subject to Joint Review: Basic Section90130:Medical systems-related , Basic Section90140:Medical technology assessment-related
    • Research Institution
      The University of Tokyo
  •  Automated AI measurement of body composition indices and its ability to predict prognosis of malignant tumors and other diseases in a large Japanese cohort.

    • Principal Investigator
      五ノ井 渉
    • Project Period (FY)
      2024 – 2027
    • Research Category
      Grant-in-Aid for Scientific Research (C)
    • Review Section
      Basic Section 52040:Radiological sciences-related
    • Research Institution
      The University of Tokyo
  •  Automatic creation of a large amount of virtual normal and abnormal medical imagesPrincipal Investigator

    • Principal Investigator
      Hanaoka Shouhei
    • 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 2023 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] 病変を埋め込んだ人工学習データによる異常検知のための新たな損失関数の提案 ~ Normal/Abnormal Contrastive (NAC) loss ~2023

    • Author(s)
      花岡 昇平, 野村 行弘, 柴田 寿一, 竹永 智美, 吉川 健啓, 林 直人, 阿部 修
    • Organizer
      電子情報通信学会 医用画像研究会 / JAMIT frontier
    • Data Source
      KAKENHI-PROJECT-21K12722
  • [Presentation] Automatic measurement of the muscle cross-sectional area on the 1st and 3rd lumbar vertebra levels by two U-nets2023

    • Author(s)
      Hanaoka S., Gonoi W., Inui S., Akamatsu N., Nomura Y., Takenaga T., Miki S., Yoshikawa T.,Hayashi N., Sugawara K., Taguchi S., Kishitani K., Kume H., Kawai T., Nakagawa T., Abe O.
    • Organizer
      Computer Assisted Radiology and Surgery (CARS) 2023
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-21K12722
  • [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
  • 1.  五ノ井 渉 (60631174)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 2.  田口 慧 (40625737)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 3.  濱田 毅 (90723461)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 4.  菅原 弘太郎 (90914812)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results

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