Takahashi Satoshi 高橋慧

Researcher Number	00852120
Affiliation (Current)	2026: 国立研究開発法人理化学研究所, 革新知能統合研究センター, 上級研究員
Affiliation (based on the past Project Information) *help	2026: 国立研究開発法人理化学研究所, 革新知能統合研究センター, 上級研究員 2024: 国立研究開発法人理化学研究所, 革新知能統合研究センター, 上級研究員 2021 – 2023: 国立研究開発法人理化学研究所, 革新知能統合研究センター, 研究員 2020: 国立研究開発法人理化学研究所, 革新知能統合研究センター, 特別研究員
Review Section/Research Field	Principal Investigator Basic Section 56010:Neurosurgery-related / Basic Section 90130:Medical systems-related Except Principal Investigator Basic Section 56010:Neurosurgery-related
Keywords	Principal Investigator 神経膠腫 / Glioma / glioma / Radiomics / MRI / 機械学習モデル / IDH変異 / 脳腫瘍 / Deep generative model / radiogenomics … More / 深層生成モデル / CycleGAN / radiomics / Domain shift problem / AI / 医療用画像 / domain shift / 機械学習 / Domain shift / Deep learning / Radiogenomics / 深層学習 … More Except Principal Investigator 解剖 / 人工知能 / segmentation / ３D画像 / 脳神経外科手術 / auto-detection / deep learning / simulation / virtual reality / 3D / 手術シミュレーション / 機械学習 / ３D virtual reality image / 画像認識 / ディープラーニング / AI / 経蝶形骨洞手術 / 頭蓋底腫瘍 Less

マルチエージェント協調型Local LLMによる高精度臨床試験マッチングシステムの開発Principal Investigator
- Principal Investigator
  
  高橋慧
- Project Period (FY)
  2026 – 2028
- Research Category
  
  Grant-in-Aid for Scientific Research (C)
- Review Section
  
  Basic Section 90130:Medical systems-related
- Research Institution
  Institute of Physical and Chemical Research
術者の“4次元的思考”をサポートする人工知能搭載脳神経外科手術支援システムの開発
- Principal Investigator
  
  辛正廣
- Project Period (FY)
  2024 – 2025
- Research Category
  
  Grant-in-Aid for Scientific Research (B)
- Review Section
  
  Basic Section 56010:Neurosurgery-related
- Research Institution
  Teikyo University
Development of Radiomics Analysis Methods with Enhanced Generalization Performance Using Deep Generative ModelsPrincipal Investigator
- Principal Investigator
  
  Takahashi Satoshi
- Project Period (FY)
  2022 – 2024
- Research Category
  
  Grant-in-Aid for Early-Career Scientists
- Review Section
  
  Basic Section 56010:Neurosurgery-related
- Research Institution
  Institute of Physical and Chemical Research
Radiomics in gliomaPrincipal Investigator
- Principal Investigator
  
  Takahashi Satoshi
- Project Period (FY)
  2020 – 2021
- Research Category
  
  Grant-in-Aid for Early-Career Scientists
- Review Section
  
  Basic Section 56010:Neurosurgery-related
- Research Institution
  Institute of Physical and Chemical Research

All 2024 2023 2022 2021 2020 2007

All Journal Article Presentation Book

[Book] アロスエルゴン Vol.1 No.3　AIの入門から応用、将来の展望ー医療の現場に進出するAIに対処するために2021
- Author(s)
  鎌谷直之、田中順治、冨田桂公、高橋　慧、高橋雅道、岩藤和広、佐野元昭、猪俣武範、國吉保孝、福永　淳、松根彰志、安藤智暁、柳　裕一郎
- Total Pages
  128
- Publisher
  クリニコ出版
- ISBN
  9784910396187
- Data Source
  KAKENHI-PROJECT-20K17982
[Journal Article] Comparison of Vision Transformers and Convolutional Neural Networks in Medical Image Analysis: A Systematic Review2024
- Author(s)
  Takahashi Satoshi、Sakaguchi Yusuke、Kouno Nobuji、Takasawa Ken、Ishizu Kenichi、Akagi Yu、Aoyama Rina、Teraya Naoki、Bolatkan Amina、Shinkai Norio、Machino Hidenori、Kobayashi Kazuma、Asada Ken、Komatsu Masaaki、Kaneko Syuzo、Sugiyama Masashi、Hamamoto Ryuji
- Journal Title
  
  Journal of Medical Systems
  
  Volume: 48 Issue: 1 Pages: 84-84
- DOI
  10.1007/s10916-024-02105-8
- Peer Reviewed / Open Access
- Data Source
  KAKENHI-PROJECT-22K16700, KAKENHI-PROJECT-24K03039
[Journal Article] 今月の特集1 感染症とArtificial Intelligenceの可能性医療とArtificial Intelligenceの現在-人口減少と少子高齢化の日本での応用を見据えて2024
- Author(s)
  高橋慧、坂口雄亮、河野伸次、浜本隆二
- Journal Title
  
  臨床検査
  
  Volume: 68 Issue: 12 Pages: 1446-1452
- DOI
  10.11477/mf.1542203805
- ISSN
  0485-1420, 1882-1367
- Year and Date
  2024-12-15
- Data Source
  KAKENHI-PROJECT-22K16700
[Journal Article] Assessing Versatile Machine Learning Models for Glioma Radiogenomic Studies across Hospitals2021
- Author(s)
  Kawaguchi Risa K.、Takahashi Masamichi、Miyake Mototaka、Kinoshita Manabu、Takahashi Satoshi、Ichimura Koichi、Hamamoto Ryuji、Narita Yoshitaka、Sese Jun
- Journal Title
  
  Cancers
  
  Volume: 13 Issue: 14 Pages: 3611-3611
- DOI
  10.3390/cancers13143611
- Peer Reviewed / Open Access
- Data Source
  KAKENHI-PROJECT-19K08216, KAKENHI-PROJECT-20K17982
[Journal Article] A New Era of Neuro-Oncology Research Pioneered by Multi-Omics Analysis and Machine Learning2021
- Author(s)
  Takahashi Satoshi、Takahashi Masamichi、Tanaka Shota、Takayanagi Shunsaku、Takami Hirokazu、Yamazawa Erika、Nambu Shohei、Miyake Mototaka、Satomi Kaishi、Ichimura Koichi、Narita Yoshitaka、Hamamoto Ryuji
- Journal Title
  
  Biomolecules
  
  Volume: 11 Issue: 4 Pages: 565-565
- DOI
  10.3390/biom11040565
- Peer Reviewed / Open Access
- Data Source
  KAKENHI-PROJECT-20K17982, KAKENHI-PROJECT-19K08216
[Journal Article] Fine-Tuning Approach for Segmentation of Gliomas in Brain Magnetic Resonance Images with a Machine Learning Method to Normalize Image Differences among Facilities2021
- Author(s)
  Takahashi Satoshi、Takahashi Masamichi、Kinoshita Manabu、et al
- Journal Title
  
  Cancers
  
  Volume: 13 Issue: 6 Pages: 1415-1415
- DOI
  10.3390/cancers13061415
- Peer Reviewed / Open Access
- Data Source
  KAKENHI-PROJECT-19K09526, KAKENHI-PROJECT-20K17982, KAKENHI-PROJECT-19K09488, KAKENHI-PROJECT-20H03792
[Journal Article] Predicting Deep Learning Based Multi-Omics Parallel Integration Survival Subtypes in Lung Cancer Using Reverse Phase Protein Array Data2020
- Author(s)
  Takahashi Satoshi、Asada Ken、Takasawa Ken、Shimoyama Ryo、Sakai Akira、Bolatkan Amina、Shinkai Norio、Kobayashi Kazuma、Komatsu Masaaki、Kaneko Syuzo、Sese Jun、Hamamoto Ryuji
- Journal Title
  
  Biomolecules
  
  Volume: 10 Issue: 10 Pages: 1460-1460
- DOI
  10.3390/biom10101460
- Peer Reviewed / Open Access
- Data Source
  KAKENHI-PROJECT-20K17982, KAKENHI-PROJECT-18K05550, KAKENHI-PROJECT-18K11542
[Journal Article] 目次2007
- Author(s)
  高橋　慧、高橋雅道、河野伸次、高澤建、田中將太、辛正廣、成田善孝、浜本隆二
- Journal Title
  
  Japanese Journal of Neurosurgery
  
  Volume: 16 Issue: 12 Pages: Cover11
- DOI
  10.7887/jcns.16.Cover11
- NAID
  130006820182
- ISSN
  0917-950X, 2187-3100
- Language
  Japanese
- Peer Reviewed
- Data Source
  KAKENHI-PROJECT-22K16700
[Presentation] Deep-Learning-Based Reconstruction of High b-Value Diffusion Weighted Images of Malignant Brain Tumors.2024
- Author(s)
  坂口雄亮、高橋慧、石黒尚明、鈴木雄一、高橋雅道、高柳俊作、三宅基隆、高見浩数、田中將太、成田善孝、斉藤延人、浜本隆二
- Organizer
  第83回日本癌学会学術総会
- Data Source
  KAKENHI-PROJECT-22K16700
[Presentation] MRIより神経膠腫のIDH変異を予測する多モデル多施設性能比較試験2024
- Author(s)
  高橋慧, 高橋雅道, 木下学, 三宅基隆, 瀬々潤, 市村幸一, 成田善孝, グリオーマ分子診断コンソーシアム, 浜本隆二
- Organizer
  第83回日本脳神経外科学会総会
- Data Source
  KAKENHI-PROJECT-22K16700
[Presentation] 深層学習に基づく悪性脳腫瘍における拡散MRI技術の効率化2024
- Author(s)
  坂口雄亮、高橋慧、石黒尚明、鈴木雄一、高見浩数、高橋雅道、高柳俊作、三宅基隆、野村昌志、北川陽介、田中將太、成田善孝、斉藤延人、浜本隆二
- Organizer
  第83回日本脳神経外科学会総会
- Data Source
  KAKENHI-PROJECT-22K16700
[Presentation] 深層学習に基づく悪性脳腫瘍における拡散MRI技術の効率化2024
- Author(s)
  坂口雄亮、高橋慧、石黒尚明、鈴木雄一、高見浩数、高橋雅道、高柳俊作、三宅基隆、野村昌志、北川陽介、田中將太、成田善孝、斉藤延人、浜本隆二
- Organizer
  第42回日本脳腫瘍学会
- Data Source
  KAKENHI-PROJECT-22K16700
[Presentation] Visual transformer モデルを用いたIDH変異予測モデルの多施設性能比較試験2023
- Author(s)
  高橋　慧
- Organizer
  第41回日本脳腫瘍学会
- Data Source
  KAKENHI-PROJECT-22K16700
[Presentation] Robustness and Explainability of Visual Transformers and Convolutional Neural Networks in Glioma Radiogenomics Tasks2023
- Author(s)
  高橋　慧
- Organizer
  第82回日本癌学会学術総会
- Data Source
  KAKENHI-PROJECT-22K16700
[Presentation] MRIより神経膠腫のIDH変異を予測する2つの深層学習モデルの多施設性能比較試験2023
- Author(s)
  高橋　慧
- Organizer
  第82回日本脳神経外科学会総会
- Data Source
  KAKENHI-PROJECT-22K16700
[Presentation] CycleGAN can be a solution to develop robust IDH mutation predicting model.2022
- Author(s)
  高橋　慧
- Organizer
  第81回日本癌学会学術総会
- Data Source
  KAKENHI-PROJECT-22K16700
[Presentation] 深層生成モデルのRadiogenomicsへの応用2022
- Author(s)
  高橋　慧
- Organizer
  第40回日本脳腫瘍学会学術集会
- Data Source
  KAKENHI-PROJECT-22K16700
[Presentation] 多施設で運用可能なMRIを用いた脳腫瘍遺伝子診断装置開発のための初期検討 -施設間画像差の可視化-2022
- Author(s)
  高橋　慧
- Organizer
  第4回日本メディカルAI学会学術集会
- Data Source
  KAKENHI-PROJECT-22K16700
[Presentation] 多施設で運用可能なMRIを用いた脳腫瘍遺伝子診断装置開発のためのCycle GANの応用可能性2022
- Author(s)
  高橋　慧
- Organizer
  日本脳神経外科学会第81回学術総会
- Data Source
  KAKENHI-PROJECT-22K16700
[Presentation] Initial Result of Develop Robust Deep Learning Model for Detecting Genomic Status in Gliomas Against Image Differences among Facilities2021
- Author(s)
  Satoshi Takahashi
- Organizer
  SNO 20222 Anual meeting
- Data Source
  KAKENHI-PROJECT-20K17982
[Presentation] 多施設間の画像差に対して頑強なセグメンテーション方法の開発2021
- Author(s)
  高橋　慧
- Organizer
  第３回日本メディカルAI学会学術総会
- Data Source
  KAKENHI-PROJECT-20K17982
[Presentation] ドメインシフトによる性能の低下に耐えうる脳腫瘍領域の自動segmentation法の開発2021
- Author(s)
  高橋　慧
- Organizer
  生命医薬情報学連合大会
- Data Source
  KAKENHI-PROJECT-20K17982
[Presentation] Development of an automatic segmentation machine learning model for brain tumor MR images that can be used at multiple domains2021
- Author(s)
  Satoshi Takahashi
- Organizer
  JCA-AACR joint meeting
- Data Source
  KAKENHI-PROJECT-20K17982
[Presentation] Initial Investigation to Developing Robust Deep Learning Model Against Image Differences among Facilities2021
- Author(s)
  高橋　慧
- Organizer
  第59回癌治療学会
- Data Source
  KAKENHI-PROJECT-20K17982
[Presentation] 多施設にて適応可能な頑強なMRIを用いた遺伝子診断方法の為の初期検討2021
- Author(s)
  高橋　慧
- Organizer
  脳神経外科学会学術総会
- Data Source
  KAKENHI-PROJECT-20K17982
[Presentation] 多施設間の画像差を埋めるFine-tuning方法の開発2020
- Author(s)
  高橋　慧
- Organizer
  第79回日本癌学会学術総会
- Data Source
  KAKENHI-PROJECT-20K17982
[Presentation] Developing automatic segmentation method for brain tumor MR images that can be used at multiple facilities2020
- Author(s)
  Takahashi Satoshi、Takahashi Masamichi、Hamamoto Ryuji et.al.
- Organizer
  2020 SNO Annual Meeting
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-20K17982
[Presentation] 多施設にて使用可能な脳腫瘍領域の自動segmentation法の開発2020
- Author(s)
  高橋　慧
- Organizer
  日本脳神経外科学会第79回学術総会
- Data Source
  KAKENHI-PROJECT-20K17982

1. 辛正廣 (70302726)

# of Collaborated Projects: 1 results

# of Collaborated Products: 0 results
2. 後藤芳明 (10933608)

# of Collaborated Projects: 1 results

# of Collaborated Products: 0 results
3. 金太一 (90447392)

# of Collaborated Projects: 1 results

# of Collaborated Products: 0 results
4. 宇野健志 (90459397)

# of Collaborated Projects: 1 results

# of Collaborated Products: 0 results
5. 新谷祐貴 (20844616)

# of Collaborated Projects: 1 results

# of Collaborated Products: 0 results
6. KINOSHITA Manabu

# of Collaborated Projects: 0 results

# of Collaborated Products: 1 results
7. 三宅基隆

# of Collaborated Projects: 0 results

# of Collaborated Products: 1 results
8. 向井まさみ

# of Collaborated Projects: 0 results

# of Collaborated Products: 1 results

Takahashi Satoshi 高橋 慧

Research Projects

Research Products

Co-Researchers

マルチエージェント協調型Local LLMによる高精度臨床試験マッチングシステムの開発Principal Investigator

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

術者の“4次元的思考”をサポートする人工知能搭載脳神経外科手術支援システムの開発

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

Development of Radiomics Analysis Methods with Enhanced Generalization Performance Using Deep Generative ModelsPrincipal Investigator

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

Radiomics in gliomaPrincipal Investigator

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

[Book] アロスエルゴン Vol.1 No.3 AIの入門から応用、将来の展望ー医療の現場に進出するAIに対処するために2021

Author(s)

Total Pages

Publisher

ISBN

Data Source

[Journal Article] Comparison of Vision Transformers and Convolutional Neural Networks in Medical Image Analysis: A Systematic Review2024

Author(s)

Journal Title

DOI

Data Source

[Journal Article] 今月の特集1 感染症とArtificial Intelligenceの可能性 医療とArtificial Intelligenceの現在-人口減少と少子高齢化の日本での応用を見据えて2024

Author(s)

Journal Title

DOI

ISSN

Year and Date

Data Source

[Journal Article] Assessing Versatile Machine Learning Models for Glioma Radiogenomic Studies across Hospitals2021

Author(s)

Journal Title

DOI

Data Source

[Journal Article] A New Era of Neuro-Oncology Research Pioneered by Multi-Omics Analysis and Machine Learning2021

Author(s)

Journal Title

DOI

Data Source

[Journal Article] Fine-Tuning Approach for Segmentation of Gliomas in Brain Magnetic Resonance Images with a Machine Learning Method to Normalize Image Differences among Facilities2021

Author(s)

Journal Title

DOI

Data Source

[Journal Article] Predicting Deep Learning Based Multi-Omics Parallel Integration Survival Subtypes in Lung Cancer Using Reverse Phase Protein Array Data2020

Author(s)

Journal Title

DOI

Data Source

[Journal Article] 目次2007

Author(s)

Journal Title

DOI

NAID

ISSN

Language

Data Source

[Presentation] Deep-Learning-Based Reconstruction of High b-Value Diffusion Weighted Images of Malignant Brain Tumors.2024

Author(s)

Organizer

Data Source

[Presentation] MRIより神経膠腫のIDH変異を予測する多モデル多施設性能比較試験2024

Author(s)

Takahashi Satoshi 高橋慧

[Book] アロスエルゴン Vol.1 No.3　AIの入門から応用、将来の展望ー医療の現場に進出するAIに対処するために2021

[Journal Article] 今月の特集1 感染症とArtificial Intelligenceの可能性医療とArtificial Intelligenceの現在-人口減少と少子高齢化の日本での応用を見据えて2024

[Presentation] 多施設にて適応可能な頑強なMRIを用いた遺伝子診断方法の為の初期検討2021