Probabilistic Tracking

Probabilistic Tracking is a computational framework within cell tracking systems that models the uncertainty in cell motion and identity over time by assigning probabilities to possible trajectories, distinguishing itself from deterministic approaches through its explicit representation of tracking ambiguity using statistical inference.

232

Publications

13.6K

Citations

718

Authors

308

Institutions

Publications per year

2017–2026

44

Authors

718

  1. WJ
    Wiro J. Niessen

    Erasmus MC, Netherlands

    8 publications · 440 citations

    8

    h-index

  2. IS
    Ihor Smal

    Erasmus MC, Netherlands

    8 publications · 440 citations

    8

    h-index

  3. EM
    Erik Meijering

    Erasmus MC, Netherlands

    8 publications · 440 citations

    8

    h-index

  4. WJ
    William J. Godinez

    Heidelberg University, Germany

    5 publications · 262 citations

    5

    h-index

  5. KR
    Karl Rohr

    Heidelberg University, Germany

    4 publications · 146 citations

    4

    h-index

1–5 of 718

Venues

  1. 9

    h-index

  2. IEEE Transactions on Medical Imaging

    7 publications · 1.1K citations

    7

    h-index

  3. Medical Image Analysis

    7 publications · 498 citations

    7

    h-index

  4. 6

    h-index

  5. IEEE Transactions on Image Processing

    5 publications · 220 citations

    5

    h-index

1–5