Deep Learning-based Registration

Deep Learning-Based Registration is a type of image registration method that leverages deep neural networks to automatically learn and optimize the spatial alignment of images by capturing complex, nonlinear transformations through data-driven feature representations.

367

Publications

27.1K

Citations

1.5K

Authors

581

Institutions

Publications per year

2017–2026

352

Authors

1.5K

  1. DS
    Dinggang Shen

    University of North Carolina at Chapel Hill, United States

    12 publications · 1.4K citations

    11

    h-index

  2. LJ
    Licheng Jiao

    Xidian University, China

    10 publications · 738 citations

    10

    h-index

  3. PY
    Pew‐Thian Yap

    University of North Carolina at Chapel Hill, United States

    7 publications · 628 citations

    7

    h-index

  4. AV
    Adrian V. Dalca

    Harvard University, United States

    7 publications · 194 citations

    7

    h-index

  5. WJ
    Walter J. Curran

    Emory University, United States

    7 publications · 425 citations

    7

    h-index

1–5 of 1.5K

Venues

  1. arXiv (Cornell University)

    Repository · 36 publications · 1.5K citations

    18

    h-index

  2. IEEE Transactions on Medical Imaging

    16 publications · 942 citations

    15

    h-index

  3. Medical Image Analysis

    14 publications · 1.6K citations

    14

    h-index

  4. Medical Physics

    12 publications · 408 citations

    12

    h-index

  5. 10

    h-index

1–5