Computational Tissue Classification

Computational Tissue Classification is a computational method that distinguishes tissue types by analyzing optical biopsy data through algorithmic models trained to identify morphological and molecular features indicative of pathological states.

274

Publications

16.8K

Citations

1.4K

Authors

594

Institutions

Publications per year

2017–2026

117

Authors

1.4K

  1. DL
    Dzung L. Pham

    Johns Hopkins University, United States

    5 publications · 199 citations

    5

    h-index

  2. RB
    Rohit Bhargava

    University of Illinois Urbana-Champaign, United States

    5 publications · 128 citations

    5

    h-index

  3. HW
    Hazem Wannous

    Université de Lille, France

    4 publications · 241 citations

    4

    h-index

  4. LM
    Lena Maier‐Hein

    German Cancer Research Center, Germany

    4 publications · 99 citations

    4

    h-index

  5. HK
    Hannes Kenngott

    Heidelberg University, Germany

    3 publications · 49 citations

    3

    h-index

1–5 of 1.4K

Venues

  1. 10

    h-index

  2. Scientific Reports

    10 publications · 498 citations

    10

    h-index

  3. IEEE Transactions on Medical Imaging

    9 publications · 2K citations

    9

    h-index

  4. Journal of Biomedical Optics

    7 publications · 424 citations

    7

    h-index

  5. Biomedical Optics Express

    BOE · 7 publications · 359 citations

    7

    h-index

1–5