Retinal Image Preprocessing

Retinal Image Preprocessing is a computational method in visual neuroscience that enhances raw retinal image data by removing noise, correcting optical distortions, and normalizing illumination to optimize downstream neural signal encoding and feature extraction in biological or artificial vision systems.

160

Publications

6.6K

Citations

671

Authors

280

Institutions

Publications per year

2017–2026

89

Authors

671

  1. YH
    Yuji Hatanaka

    Gifu University, Japan

    3 publications · 200 citations

    3

    h-index

  2. HF
    Hiroshi Fujita

    Gifu University, Japan

    3 publications · 200 citations

    3

    h-index

  3. CM
    Chisako Muramatsu

    Gifu University, Japan

    3 publications · 200 citations

    3

    h-index

  4. TY
    Tien Yin Wong

    Singapore Eye Research Institute, Singapore

    3 publications · 71 citations

    3

    h-index

  5. JL
    Jianqiang Li

    Beijing University of Technology, China

    3 publications · 163 citations

    3

    h-index

1–5 of 671

Venues

  1. Computers in Biology and Medicine

    4 publications · 234 citations

    4

    h-index

  2. Translational Vision Science & Technology

    TVST · 4 publications · 145 citations

    4

    h-index

  3. Lecture notes in computer science

    LNCS · Book series · 3 publications · 178 citations

    3

    h-index

  4. Computer Methods and Programs in Biomedicine

    3 publications · 150 citations

    3

    h-index

  5. Journal of the Optical Society of America A

    3 publications · 79 citations

    3

    h-index

1–5