Deep Learning for Cornea Microscopy Blind Deblurring
This addresses the issue of obtaining sharp images for ophthalmologists examining corneas, but it appears incremental as it applies an existing method to a new medical dataset.
The researchers tackled the problem of deblurring cornea scans from confocal microscopy by developing a deep-learning solution using a super-resolution network to upscale images, but no concrete results or numbers were reported in the 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.