Utilizing fully-automated 3D organ segmentation for hepatic steatosis assessment with CT attenuation-based parameters - Top-Institutions - MDSpire

Utilizing fully-automated 3D organ segmentation for hepatic steatosis assessment with CT attenuation-based parameters

  • By

  • Jeongin Yoo

  • Ijin Joo

  • Sun Kyung Jeon

  • Junghoan Park

  • Soon Ho Yoon

  • February 23, 2024

  • 0 min

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Top Institutions in Radiology

Brief introduction explaining scope and methodology.

  • #1

    Mayo Clinic
    Mayo Clinic

    Rochester, MN

    Key Differentiators

    • Radiology
    • Hepatology
    • Medical Imaging AI

  • #2

    Massachusetts General Hospital
    Massachusetts General Hospital

    Boston, MA

    Key Differentiators

    • Radiology
    • Hepatology
    • Biomedical Engineering

  • #3

    Johns Hopkins University
    Johns Hopkins University

    Baltimore, MD

    Key Differentiators

    • Radiology
    • Hepatology
    • Computer Science

  • #4

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

    San Francisco, CA

    Key Differentiators

    • Radiology
    • Hepatology
    • Medical Informatics

  • #5

    Stanford University
    Stanford University

    Stanford, CA

    Key Differentiators

    • Radiology
    • Hepatology
    • Artificial Intelligence

Original Source(s)

Utilizing fully-automated 3D organ segmentation for hepatic steatosis assessment with CT attenuation-based parameters

  • by Jeongin Yoo, Ijin Joo, Sun Kyung Jeon, Junghoan Park, Soon Ho Yoon

  • February 23, 2024

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