Learning-based endovascular navigation through the use of non-rigid registration for collaborative robotic catheterization - Top-Institutions - MDSpire

Learning-based endovascular navigation through the use of non-rigid registration for collaborative robotic catheterization

  • By

  • Wenqiang Chi

  • Jindong Liu

  • Hedyeh Rafii-Tari

  • Celia Riga

  • Colin Bicknell

  • Guang-Zhong Yang

  • April 12, 2018

  • 0 min

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Top Institutions in Surgery

Brief introduction explaining scope and methodology.

  • #1

    Stanford University
    Stanford University

    Stanford, CA

    Key Differentiators

    • Interventional Radiology
    • Robotics
    • Machine Learning

  • #2

    Johns Hopkins University
    Johns Hopkins University

    Baltimore, MD

    Key Differentiators

    • Interventional Radiology
    • Biomedical Engineering
    • Robotics

  • #3

    Massachusetts General Hospital / Harvard Medical School
    Massachusetts General Hospital / Harvard Medical School

    Boston, MA

    Key Differentiators

    • Interventional Radiology
    • Robotic Surgery
    • Medical Imaging

  • #4

    University of California, San Diego (UCSD)
    University of California, San Diego (UCSD)

    San Diego, CA

    Key Differentiators

    • Robotics
    • Interventional Radiology
    • Computer Science

  • #5

    Mayo Clinic
    Mayo Clinic

    Rochester, MN

    Key Differentiators

    • Interventional Radiology
    • Robotic Surgery
    • Clinical Research

Original Source(s)

Learning-based endovascular navigation through the use of non-rigid registration for collaborative robotic catheterization

  • by Wenqiang Chi, Jindong Liu, Hedyeh Rafii-Tari, Celia Riga, Colin Bicknell, Guang-Zhong Yang

  • April 12, 2018

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