Tensor Field Feature Extraction

Tensor Field Feature Extraction is a computational methodology within tensor field analysis that identifies and isolates structurally significant patterns, such as tensor invariants, eigenvector fields, or degenerate points, to enable the interpretation and visualization of underlying physical phenomena in multidimensional data.

25

Publications

1.7K

Citations

81

Authors

50

Institutions

Publications per year

2017–2026

7

Authors

81

  1. GK
    Gordon Kindlmann

    University of Chicago, United States

    3 publications · 399 citations

    3

    h-index

  2. EZ
    Eugene Zhang

    Oregon State University, United States

    3 publications · 58 citations

    3

    h-index

  3. YZ
    Yue Zhang

    Oregon State University, United States

    3 publications · 58 citations

    3

    h-index

  4. AP
    Alex Pang

    University of California, Santa Cruz, United States

    2 publications · 118 citations

    2

    h-index

  5. DM
    David M. Weinstein

    University of Utah, United States

    2 publications · 341 citations

    2

    h-index

1–5 of 81

Venues

  1. IEEE Transactions on Visualization and Computer Graphics

    TVCG · 5 publications · 170 citations

    5

    h-index

  2. Medical Image Analysis

    2 publications · 86 citations

    2

    h-index

  3. Journal of Magnetic Resonance

    JMR · 1 publications · 145 citations

    1

    h-index

  4. Pattern Recognition

    1 publications · 59 citations

    1

    h-index

  5. Human Brain Mapping

    1 publications · 12 citations

    1

    h-index

1–5