Retinal Feature Detection

Retinal Feature Detection is a computational method in computer vision that identifies and localizes specific morphological structures or abnormalities in retinal imagery by analyzing pixel-level patterns through image processing or machine learning techniques.

973

Publications

58.2K

Citations

3.1K

Authors

1.1K

Institutions

Publications per year

2017–2026

499

Authors

3.1K

  1. JL
    Jiang Liu

    Institute for Infocomm Research, Singapore

    17 publications · 647 citations

    15

    h-index

  2. TY
    Tien Yin Wong

    Singapore Eye Research Institute, Singapore

    19 publications · 758 citations

    15

    h-index

  3. MU
    Muhammad Usman Akram

    National University of Sciences and Technology, Pakistan

    14 publications · 660 citations

    12

    h-index

  4. MH
    Michael H. Goldbaum

    University of California San Diego, United States

    12 publications · 5.2K citations

    12

    h-index

  5. DW
    Damon Wing Kee Wong

    Singapore Eye Research Institute, Singapore

    12 publications · 357 citations

    12

    h-index

1–5 of 3.1K

Venues

  1. Biomedical Signal Processing and Control

    23 publications · 892 citations

    18

    h-index

  2. IEEE Transactions on Medical Imaging

    16 publications · 6.8K citations

    16

    h-index

  3. Multimedia Tools and Applications

    18 publications · 876 citations

    16

    h-index

  4. Computer Methods and Programs in Biomedicine

    15 publications · 1.4K citations

    15

    h-index

  5. IEEE Access

    14 publications · 753 citations

    14

    h-index

1–5