Homology-feature-assisted quantification of fibrotic lesions in computed tomography images: a proof of concept for CT image feature-based prediction for gene-expression-distribution - Top-Institutions - MDSpire

Homology-feature-assisted quantification of fibrotic lesions in computed tomography images: a proof of concept for CT image feature-based prediction for gene-expression-distribution

  • By

  • Kentaro Doi

  • Hodaka Numasaki

  • Yusuke Anetai

  • Yayoi Natsume-Kitatani

  • May 28, 2025

  • 0 min

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Top Institutions in Surgery

Brief introduction explaining scope and methodology.

  • #1

    National Jewish Health
    National Jewish Health

    Denver, CO

    Key Differentiators

    • Pulmonology
    • Interstitial Lung Disease
    • Thoracic Radiology
    • Computational Imaging

  • #2

    Mayo Clinic
    Mayo Clinic

    Rochester, MN

    Key Differentiators

    • Pulmonology
    • Radiology
    • Computational Medicine

  • #3

    Johns Hopkins University
    Johns Hopkins University

    Baltimore, MD

    Key Differentiators

    • Pulmonology
    • Radiology
    • Biomedical Engineering

  • #4

    University of California, San Francisco (UCSF)
    University of California, San Francisco (UCSF)

    San Francisco, CA

    Key Differentiators

    • Pulmonology
    • Radiology
    • Bioinformatics

  • #5

    Brigham and Women’s Hospital / Harvard Medical School
    Brigham and Women’s Hospital / Harvard Medical School

    Boston, MA

    Key Differentiators

    • Pulmonology
    • Radiology
    • Computational Biology

Original Source(s)

Homology-feature-assisted quantification of fibrotic lesions in computed tomography images: a proof of concept for CT image feature-based prediction for gene-expression-distribution

  • by Kentaro Doi, Hodaka Numasaki, Yusuke Anetai, Yayoi Natsume-Kitatani

  • May 28, 2025

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