Hierarchical Registration

Hierarchical Registration is a registration method that operates by sequentially aligning data across multiple scales or levels of resolution, beginning with coarse-level alignment to guide finer-level refinements.

39

Publications

3.6K

Citations

144

Authors

69

Institutions

Publications per year

2017–2026

10

Authors

144

  1. DS
    Dinggang Shen

    University of North Carolina at Chapel Hill, United States

    6 publications · 181 citations

    6

    h-index

  2. GW
    Guorong Wu

    University of North Carolina at Chapel Hill, United States

    4 publications · 124 citations

    4

    h-index

  3. QW
    Qian Wang

    Shanghai Jiao Tong University, China

    3 publications · 106 citations

    3

    h-index

  4. DR
    Daniel Rueckert

    Imperial College London, United Kingdom

    2 publications · 376 citations

    2

    h-index

  5. DL
    D. Louis Collins

    Montreal Neurological Institute and Hospital, Canada

    2 publications · 1K citations

    2

    h-index

1–5 of 144

Venues

  1. Lecture notes in computer science

    LNCS · Book series · 4 publications · 67 citations

    4

    h-index

  2. Pattern Recognition

    2 publications · 500 citations

    2

    h-index

  3. Human Brain Mapping

    2 publications · 1K citations

    2

    h-index

  4. Computers & Mathematics with Applications

    2 publications · 25 citations

    2

    h-index

  5. Medical Image Analysis

    2 publications · 120 citations

    2

    h-index

1–5