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Development of image biomarker for the diagnosis of lung cancer in PET/CT and pathological images

Research Project

Project/Area Number 17K09070
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Research Field Medical Physics and Radiological Technology
Research InstitutionFujita Health University

Principal Investigator

Teramoto Atsushi  藤田医科大学, 保健学研究科, 教授 (00513780)

Co-Investigator(Kenkyū-buntansha) 塚本 徹哉  藤田医科大学, 医学部, 教授 (00236861)
今泉 和良  藤田医科大学, 医学部, 教授 (50362257)
外山 宏  藤田医科大学, 医学部, 教授 (90247643)
Project Period (FY) 2017-04-01 – 2020-03-31
Project Status Completed (Fiscal Year 2019)
Budget Amount *help
¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000)
Fiscal Year 2019: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2018: ¥2,470,000 (Direct Cost: ¥1,900,000、Indirect Cost: ¥570,000)
Fiscal Year 2017: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Keywords人工知能 / 医用画像 / 肺がん / 診断 / PET/CT / 病理画像 / 深層学習 / 鑑別 / 敵対的生成ネットワーク / 自動分類 / 肺癌 / Classification / Deep learning / 医療・福祉 / 画像
Outline of Final Research Achievements

Lung cancer has become the leading cause of death and has become a social problem. The purpose of this study was to develop a technology that can diagnose lung diseases with high accuracy using PET/CT images taken by differential diagnosis and microscopic images taken by definitive diagnosis. In this study, we first collected image data of lung disease patients. Then, the image features are calculated from them, and the benign/malignant classification of the lung nodule and the histological classification of the lung cancer are performed based on the calculated image features using a machine learning method. As a result of the evaluation, it was confirmed that the classification accuracy was improved by combining a plurality of images.

Academic Significance and Societal Importance of the Research Achievements

PET/CT画像のような放射線画像と、病理画像を対象とした深層学習の研究は多数行われているが、それらを組合せた研究は実施例が極めて少ない。本研究は深層学習や統計的手法を駆使した診断支援処理を実現しようとしたものであり、学術的な意義がある。また、画像診断を専門としない主治医にとって,本研究で算出できるようにした画像バイオマーカーは病変部の特徴を把握しやすく,予後判定や治療方針の決定にも活用できる.これらの技術によって肺がんの早期診断や正確な診断が実現する可能性が高く、患者のQOL向上や医療費の削減につながる。

Report

(4 results)
  • 2019 Annual Research Report   Final Research Report ( PDF )
  • 2018 Research-status Report
  • 2017 Research-status Report
  • Research Products

    (39 results)

All 2020 2019 2018 2017 Other

All Int'l Joint Research (2 results) Journal Article (12 results) (of which Int'l Joint Research: 1 results,  Peer Reviewed: 10 results,  Open Access: 5 results) Presentation (19 results) (of which Int'l Joint Research: 15 results) Book (5 results) Remarks (1 results)

  • [Int'l Joint Research] National Institute of Health/NVIDIA(米国)

    • Related Report
      2019 Annual Research Report
  • [Int'l Joint Research] National Institute of Health(米国)

    • Related Report
      2017 Research-status Report
  • [Journal Article] Multiplanar analysis for pulmonary nodule classification in CT images using deep convolutional neural network and generative adversarial networks2020

    • Author(s)
      Y.Onishi, A.Teramoto, M.Tsujimoto, T.Tsukamoto, K.Saito, H.Toyama, K.Imaizumi, H.Fujita
    • Journal Title

      International Journal of Computer Assisted Radiology and Surgery

      Volume: 15 Issue: 1 Pages: 173-178

    • DOI

      10.1007/s11548-019-02092-z

    • Related Report
      2019 Annual Research Report
    • Peer Reviewed
  • [Journal Article] Deep learning approach to classification of lung cytological images: Two-step training using actual and synthesized images by progressive growing of generative adversarial networks2020

    • Author(s)
      A.Teramoto, T.Tsukamoto, A.Yamada, Y.Kiriyama, K.Imaizumi, K.Saito, H.Fujita
    • Journal Title

      PLoS ONE

      Volume: 15 Issue: 3 Pages: e0229951-e0229951

    • DOI

      10.1371/journal.pone.0229951

    • Related Report
      2019 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] Pilot Study on Automated Classification of Lung Cancer Types from Liquid-Based Cytological Image and Electronic Medical Record2019

    • Author(s)
      山田あゆみ, 寺本篤司, 桐山諭和, 塚本徹哉, 今泉和良, 星雅人, 齋藤邦明, 藤田広志
    • Journal Title

      Medical Imaging Technology

      Volume: 37 Issue: 5 Pages: 230-234

    • DOI

      10.11409/mit.37.230

    • NAID

      130007752665

    • ISSN
      0288-450X, 2185-3193
    • Year and Date
      2019-11-25
    • Related Report
      2019 Annual Research Report
    • Peer Reviewed
  • [Journal Article] Automated classification of benign and malignant cells from lung cytological images using deep convolutional neural network2019

    • Author(s)
      A.Teramoto, A.Yamada, Y.Kiriyama, T.Tsukamoto, K.Yan, L.Zhang, K.Imaizumi, K.Saito, H.Fujita
    • Journal Title

      Informatics in Medicine Unlocked

      Volume: 16 Pages: 100205-100205

    • DOI

      10.1016/j.imu.2019.100205

    • Related Report
      2019 Annual Research Report
    • Peer Reviewed / Open Access / Int'l Joint Research
  • [Journal Article] Automated pulmonary nodule classification in computed tomography images using a deep convolutional neural network trained by generative adversarial networks2019

    • Author(s)
      Y.Onishi, A.Teramoto, M.Tsujimoto, T.Tsukamoto, K.Saito, H.Toyama, K.Imaizumi, H.Fujita
    • Journal Title

      BioMed Research International

      Volume: 6051939 Pages: 1-9

    • DOI

      10.1155/2019/6051939

    • Related Report
      2018 Research-status Report
    • Peer Reviewed / Open Access
  • [Journal Article] 放射線診断領域における人工知能の応用2019

    • Author(s)
      寺本篤司,
    • Journal Title

      癌と化学療法

      Volume: 46 Pages: 418-422

    • Related Report
      2018 Research-status Report
  • [Journal Article] Automated classification of pulmonary nodules through a retrospective analysis of conventional CT and two-phase PET images in patients undergoing biopsy2018

    • Author(s)
      A.Teramoto, M.Tsujimoto, T.Inoue, T.Tsukamoto, K.Imaizumi, H.Toyama, K.Saito, H.Fujita
    • Journal Title

      Asia Oceania Journal of Nuclear Medicine and Biology

      Volume: 7 Pages: 29-37

    • Related Report
      2018 Research-status Report
    • Peer Reviewed / Open Access
  • [Journal Article] Basic study on the automated detection method of skull fracture in head CT images using surface selective black-hat transform2018

    • Author(s)
      A.Yamada, A.Teramoto, K.Kudo, T.Otsuka, H.Anno, H.Fujita
    • Journal Title

      Journal of Medical Imaging and Health Informatics

      Volume: 印刷中

    • Related Report
      2017 Research-status Report
    • Peer Reviewed
  • [Journal Article] Fluctuation of quantitative values on acquisition time and the reconstruction conditions in 99mTc-SPECT2018

    • Author(s)
      M.Tsujimoto, S.Shirakawa, A.Teramoto, M.Ishiguro, K.Nakane, Y.Ida, H.Toyama
    • Journal Title

      Nuclear Medicine Communications

      Volume: 印刷中

    • Related Report
      2017 Research-status Report
    • Peer Reviewed
  • [Journal Article] 肺結節自動検出処理におけるディープラーニング応用2017

    • Author(s)
      寺本篤司
    • Journal Title

      医用画像情報学会雑誌

      Volume: 34 Pages: 54-56

    • NAID

      130006846717

    • Related Report
      2017 Research-status Report
  • [Journal Article] Automated classification of lung cancer types from cytological images using deep convolutional neural networks2017

    • Author(s)
      Atsushi Teramoto, Tetsuya Tsukamoto, Yuka Kiriyama, Hiroshi Fujita
    • Journal Title

      BioMed Research International

      Volume: 2017 Pages: 1-6

    • Related Report
      2017 Research-status Report
    • Peer Reviewed / Open Access
  • [Journal Article] Automated segmentation and detection of increased uptake regions in bone scintigraphy using SPECT/CT images2017

    • Author(s)
      Masakazu Tsujimoto, Atsushi Teramoto, Seiichiro Ota, Hiroshi Toyama, Hiroshi Fujita
    • Journal Title

      Annals of Nuclear Medicine

      Volume: 32 Pages: 197-205

    • Related Report
      2017 Research-status Report
    • Peer Reviewed
  • [Presentation] Automated Classification Method of Lung Tumor Type using Cytological Image and Clinical Record2020

    • Author(s)
      A.Yamada, A.Teramoto, Y.Kiriyama, T.Tsukamoto, K.Imaizumi, M.Hoshi, K.Saito and H. Fujita
    • Organizer
      IWAIT 2020
    • Related Report
      2019 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Hybrid Scheme of Pulmonary Nodule Classification Using Deep Convolutional Neural Network in PET/CT and Microscopic Images2019

    • Author(s)
      A.Teramoto, A.Yamada, M.Tsujimoto, T.Tsukamoto, K.Saito, H.Toyama, K.Imaizumi, H.Fujita
    • Organizer
      the 13th Asia Oceania Congress of Nuclear Medicine and Biology
    • Related Report
      2019 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Automated Classification of Pulmonary Nodules in CT Images Using Generative Adversarial Networks and Deep Convolutional Neural Networks2019

    • Author(s)
      Y.Onishi, A.Teramoto, M.Tsujimoto, T.Tsukamoto, K.Saito, H.Toyama, K.Imaizumi, H.Fujita
    • Organizer
      the 13th Asia Oceania Congress of Nuclear Medicine and Biology
    • Related Report
      2019 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Improvement of classification performance of pulmonary nodules in CT images using multiple deep convolutional generative adversarial networks2019

    • Author(s)
      Y.Onishi, A.Teramoto, M.Tsujimoto, T.Tsukamoto, K.Saito, H.Toyama, K.Imaizumi, H. Fujita
    • Organizer
      CARS 2019
    • Related Report
      2019 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Automated malignancy analysis of microscopic lung images using a deep convolutional neural net- work and generative adversarial networks2019

    • Author(s)
      A.Teramoto, A.Yamada, Y.Kiriyama, T.Tsukamoto, K.Yan, L.Zhang, K.Imaizumi, K.Saito, H.Fujita
    • Organizer
      CARS 2019
    • Related Report
      2019 Annual Research Report
    • Int'l Joint Research
  • [Presentation] What is GAN? Contribution to Radiology Using Cutting Edge Technology2019

    • Author(s)
      Y.Onishi, A.Teramoto, H.Toyama, K.Saito, H.Fujita
    • Organizer
      RSNA2019
    • Related Report
      2019 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Automated classification and segmentation of malignant pulmonary cells in the cytological image2018

    • Author(s)
      A.Teramoto, A.Yamada, Y.Kiriyama, T.Tsukamoto, Y.Ke, Z.Ling, RM.Summers, K.Saito, H.Fujita, "Automated classification and segmentation of malignant pulmonary cells in the cytological image," 4th Digit
    • Organizer
      4th Digital Pathology Congres Asia
    • Related Report
      2018 Research-status Report
    • Int'l Joint Research
  • [Presentation] Fine-tuning deep convolutional neural networks for classification of lung cancer types from cytological images2018

    • Author(s)
      T.Tsukamoto, A.Teramoto, Y.Kiriyama, A.Yamada
    • Organizer
      4th Digital Pathology Congres Asia
    • Related Report
      2018 Research-status Report
    • Int'l Joint Research
  • [Presentation] Automated classification of pulmonary nodule in CT images:Development of analysis method using multi DCNNs2018

    • Author(s)
      Y.Onishi, A.Yamada, M.Tujimoto, T.Inoue, A.Teramoto, K.Imaizumi, H.Toyama, K.Saito, H.Fujita
    • Organizer
      40th Annual International Conference of the IEEE EMBS
    • Related Report
      2018 Research-status Report
    • Int'l Joint Research
  • [Presentation] Decision support system for lung cancer using PET/CT and microscopic images2018

    • Author(s)
      A.Teramoto, A.Yamada, T.Tsukamoto, Y.Kiriyama, M.Tsujimoto, T.Inoue, K.Imaizumi, H.Toyama, K.Saito, H.Fujita
    • Organizer
      40th Annual International Conference of the IEEE EMBS
    • Related Report
      2018 Research-status Report
    • Int'l Joint Research
  • [Presentation] 3-Minute Recipe for Deep Learning: Principle, Hardware, and Software2018

    • Author(s)
      A.Teramoto, H.Fujita
    • Organizer
      RSNA2018
    • Related Report
      2018 Research-status Report
    • Int'l Joint Research
  • [Presentation] Preliminary study on the automated analysis of pulmonary nodules in early and delayed phase PET/CT images using support vector machine2017

    • Author(s)
      A.Teramoto, M.Tsujimoto, T.Inoue, T.Tsukamoto, K.Imaizumi, H.Toyama, H.Fujita
    • Organizer
      2017 Asian Nuclear Medicine Academic Forum
    • Related Report
      2017 Research-status Report
    • Int'l Joint Research
  • [Presentation] Computer aided method for the hot-spot analysis using SPECT/CT images: development of bone segmentation and hot-spot analysis2017

    • Author(s)
      M.Tsujimoto, A.Teramoto, S.Ota, M.Ishiguro, H.Toyama, H.Fujita
    • Organizer
      2017 Asian Nuclear Medicine Academic Forum
    • Related Report
      2017 Research-status Report
    • Int'l Joint Research
  • [Presentation] Automated detection of small breast tumors in dedicated breast PET images: development of adaptive thresholding technique2017

    • Author(s)
      N.Minoura, A.Teramoto, O.Yamamuro, K.Murase, A.Ito, K.Takahashi, K.Omi, M.Nishio, H.Fujita
    • Organizer
      2017 Asian Nuclear Medicine Academic Forum
    • Related Report
      2017 Research-status Report
    • Int'l Joint Research
  • [Presentation] Automated classification of lung tumors using PET/CT and microscopic images2017

    • Author(s)
      A.Teramoto, T.Tsukamoto, Y.Kiriyama, M.Tsujimoto, H.Toyama, K.Imaizumi, H.Fujita
    • Organizer
      CARS2017
    • Related Report
      2017 Research-status Report
    • Int'l Joint Research
  • [Presentation] 細胞診画像を用いた肺癌組織型の自動分類に関する研究2017

    • Author(s)
      竹内野々子, 山田あゆみ, 寺本篤司, 塚本徹哉, 藤田広志
    • Organizer
      医用画像情報学会 平成29年度年次大会
    • Related Report
      2017 Research-status Report
  • [Presentation] 肺癌細胞の自動分類処理における従来型識別処理と深層学習の識別性能比較2017

    • Author(s)
      寺本篤司, 山田あゆみ, 竹内野々子, 塚本徹哉, 藤田広志
    • Organizer
      平成29年度生体医工学会東海支部大会
    • Related Report
      2017 Research-status Report
  • [Presentation] CT画像を用いた肺結節の良悪性自動解析手法に関する検討~Deep Convolutional Neural Network を用いた識別性能の初期的評価~2017

    • Author(s)
      大西佑弥,山田あゆみ, 寺本篤司, 辻本正和, 井上敬浩, 外山宏, 今泉和良, 藤田広志
    • Organizer
      平成29年度生体医工学会東海支部大会
    • Related Report
      2017 Research-status Report
  • [Presentation] CT画像を用いたDeep convolutional neural networkによる肺結節の良悪性自動解析に関する予備的検討2017

    • Author(s)
      大西佑弥, 山田あゆみ, 寺本篤司, 辻本正和, 井上敬浩, 外山 宏, 今泉和良, 藤田広志
    • Organizer
      第10回中部放射線医療技術学術大会
    • Related Report
      2017 Research-status Report
  • [Book] Deep Learning in Medical Image Analysis, Advances in Experimental Medicine and Biology 12132019

    • Author(s)
      A.Teramoto, A.Yamada, T.Tsukamoto, K.Imaizumi, H.Toyama, K.Saito, H.Fujita
    • Total Pages
      12
    • Publisher
      Springer Nature Switzerland AG
    • Related Report
      2019 Annual Research Report
  • [Book] 医用画像ディープラーニング入門2019

    • Author(s)
      藤田広志(監修・編)
    • Total Pages
      20
    • Publisher
      オーム社
    • Related Report
      2019 Annual Research Report
  • [Book] よくわかる医用画像情報学2018

    • Author(s)
      石田隆行監修
    • Total Pages
      14
    • Publisher
      オーム社
    • ISBN
      9784274221316
    • Related Report
      2018 Research-status Report
  • [Book] Artificial Intelligence in Decision Support Systems for Diagnosis in Medical Imaging2018

    • Author(s)
      A. Teramoto and H. Fujita
    • Total Pages
      24
    • Publisher
      Springer
    • Related Report
      2017 Research-status Report
  • [Book] 医用画像情報工学2018

    • Author(s)
      藤田広志、寺本篤司、岡部哲夫 編
    • Total Pages
      230
    • Publisher
      医歯薬出版株式会社
    • Related Report
      2017 Research-status Report
  • [Remarks] Teramoto laboratory

    • URL

      http://www.fujita-hu.ac.jp/~teramoto/

    • Related Report
      2019 Annual Research Report

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Published: 2017-04-28   Modified: 2022-02-21  

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