TAKAHASHI Noriyuki

写真a

Title

Professor
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Current Affiliation Organization 【 display / non-display 】

  • Duty ,  School of Health Sciences ,  Depertment of Medical Radiology Technology ,  Professor

  • Concurrently ,  School of Medicine (Clinical Medicine) ,  Department of Radiology ,  Professor

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Graduate School 【 display / non-display 】

  • Niigata University ,  Graduate School, Division of Health Care ,  Doctor's Course ,  Completed ,  JAPAN ,  2010

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Field of expertise (Grants-in-aid for Scientific Research classification) 【 display / non-display 】

  • Radiation science

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Qualification acquired 【 display / non-display 】

  • Chief Person of Radiation Handling （first and second kind）

  • Radiological Technologist

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Papers 【 display / non-display 】

  • Explainable Analysis of Deep Learning Models for Coronavirus Disease (COVID-19) Classification with Chest X-Ray Images: Towards Practical Applications

    Eri Matsuyama, Haruyuki Watababe, Noriyuki Takahashi

    Open Journal of Medical Imaging ,  12   83 - 102 ,  2022.07

    Multiple Authorship

  • Development of an automatic multiplanar reconstruction processing method for head computed tomography

    Mitsuru Sato, Yohan Kondo, Noriyuki Takahashi, Tomomi Ohmura, Naoya Takahashi

    Journal of X-Ray Science and Technology ,  2022.04

    Multiple Authorship

    DOI

  • Prediction of an oxygen extraction fraction map by convolutional neural network: validation of input data among MR and PET images

    Keisuke Matsubara, Masanobu Ibaraki, Yuki Shinohara, Noriyuki Takahashi, Hideto Toyoshima, and Toshibumi Kinoshita

    International Journal of Computer Assisted Radiology and Surgery ,  2021.04

    Multiple Authorship

    DOI

  • Usefulness of deep learning-assisted identification of hyperdense MCA sign in acute ischemic stroke: comparison with readers' performance.

    Shinohara Y, Takahashi N, Lee Y, Ohmura T, Umetsu A, Kinoshita F, Kuya K, Kato A, Kinoshita T

    Japanese journal of radiology ,  2020.05

    Multiple Authorship ,  ISBN: 1867-1071

    DOI PubMed

  • Development of a deep learning model to identify hyperdense MCA sign in patients with acute ischemic stroke

    Shinohara Y, Takahashi N, Lee Y, Ohmura T, Kinoshita T

    Japanese Journal of Radiology ,  38 (2) 112 - 117 ,  2020.02

    Multiple Authorship

    DOI

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Books 【 display / non-display 】

  • Computed Tomography –Clinical Applications　

    InTech ,  2012.01

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Industrial Property 【 display / non-display 】

  • MEDICAL CROSS-SECTIONAL IMAGE DISPLAYING APPARATUS AND MRTHOD FOR DISPLAYING CROSS-SECTIONAL IMAGE

    Industrial Property No 2016-033721 2016 .02 .25 JP  2017.01.11  Patent No CN 107115117 B  2020.08.04 

    Patent

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Presentations 【 display / non-display 】

  • Automated scheme based deep learning to identify abnormality in dopamine transporter SPECT

    第62回日本核医学会学術総会 , 

    2022.09
    　
    　

  • Deep learning-assisted diagnosis of hyperdense MCA sign in acute ischemic stroke

    ASNR 57th annual meeting , 

    2019.05
    　
    　

  • Deep learning-assisted diagnosis of hyperdense MCA sign in acute ischemic stroke: comparison with readers’ performance

    第78回日本医学放射線学会総会 , 

    2019.04
    　
    　

  • Computerized identification of early ischemic changes in acute stroke in noncontrast CT using deep learning

    SPIE2019 medical imaging , 

    2019.02
    　
    　

  • Detection of the Ischemic Core in Multiphase-CT Angiography: Validation of Patients with Acute Ischemic Stroke

    104th Scientific Assembly and Annual Meeting of Radiological Society of North AmericaRSNA2018 , 

    2018.11
    　
    　

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