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Deep Learning for Cornea Microscopy Blind Deblurring

Computer Vision and Pattern Recognition 2020-06-26 v1

Abstract

The goal of this project is to build a deep-learning solution that deblurs cornea scans, used for medical examination. The spherical shape of the eye prevents ophtamologist from having completely sharp image. Provided with a stack of corneas from confocal images, our approach is to build a model that performs an upscaling of the images using an SR (Super Resolution) Network.

Keywords

Cite

@article{arxiv.2006.14319,
  title  = {Deep Learning for Cornea Microscopy Blind Deblurring},
  author = {Toussain Cardot and Pilar Marxer and Ivan Snozzi},
  journal= {arXiv preprint arXiv:2006.14319},
  year   = {2020}
}
R2 v1 2026-06-23T16:37:12.319Z