Improving CT-CBCT deformable image registration for cervical cancer adaptive radiotherapy using a deep learning approach - Top-Institutions - MDSpire

Improving CT-CBCT deformable image registration for cervical cancer adaptive radiotherapy using a deep learning approach

  • By

  • Chengjian Xiao

  • Chunlan Huang

  • Weixiang Lin

  • Feilong Tian

  • Youxing Zeng

  • July 6, 2026

  • 0 min

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Top Institutions in Oncology

Brief introduction explaining scope and methodology.

  • #1

    The University of Texas MD Anderson Cancer Center
    The University of Texas MD Anderson Cancer Center

    Houston, Texas

    Key Differentiators

    • Oncology
    • Radiation Oncology

  • #2

    UT Southwestern Medical Center
    UT Southwestern Medical Center

    Dallas, Texas

    Key Differentiators

    • Oncology
    • Radiation Oncology

  • #3

    Hospital I
    Hospital I

    Unknown, Unknown

    Key Differentiators

    • Radiation Oncology

  • #4

    Hospital of Stomatology, Wuhan University
    Hospital of Stomatology, Wuhan University

    Wuhan, Hubei

    Key Differentiators

    • Radiation Oncology

  • #5

    Samsung Medical Center
    Samsung Medical Center

    Seoul, South Korea

    Key Differentiators

    • Radiation Oncology

Original Source(s)

Improving CT-CBCT deformable image registration for cervical cancer adaptive radiotherapy using a deep learning approach

  • by Chengjian Xiao, Chunlan Huang, Weixiang Lin, Feilong Tian, Youxing Zeng

  • July 6, 2026

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