Classification Of Volume Data

Classification of Volume Data is a methodological framework within medical volume visualization that distinguishes volumetric datasets by assigning tissue types or anatomical structures to discrete visual representations based on scalar intensity values, gradient magnitudes, or spatial features derived from 3D imaging modalities.

136

Publications

8K

Citations

534

Authors

258

Institutions

Publications per year

2017–2026

42

Authors

534

  1. KM
    Kwan‐Liu Ma

    University of California, Davis, United States

    10 publications · 763 citations

    10

    h-index

  2. EB
    Eric B. Lum

    University of California, Davis, United States

    4 publications · 293 citations

    4

    h-index

  3. FT
    Fan-Yin Tzeng

    University of California, Davis, United States

    3 publications · 316 citations

    3

    h-index

  4. CC
    C. Correa

    University of California, Davis, United States

    3 publications · 296 citations

    3

    h-index

  5. OB
    Oleg Bondarenko

    University of Illinois Chicago, United States

    2 publications · 74 citations

    2

    h-index

1–5 of 534

Venues

  1. IEEE Transactions on Visualization and Computer Graphics

    TVCG · 12 publications · 818 citations

    12

    h-index

  2. IEEE Transactions on Medical Imaging

    8 publications · 811 citations

    8

    h-index

  3. Computer Graphics Forum

    6 publications · 201 citations

    6

    h-index

  4. NeuroImage

    4 publications · 1.1K citations

    4

    h-index

  5. Medical Image Analysis

    3 publications · 160 citations

    3

    h-index

1–5