Deep Learning for Cornea Microscopy Blind Deblurring

2020/06/25 by Toussain Cardot, Cardot, Toussain, Pilar Marxer +3
Computer Science · Engineering · #Advanced Image Fusion Techniques #Advanced Image Processing Techniques #Optical Coherence Tomography Applications #cs.CV

paper · pdf · doi:10.48550/arxiv.2006.14319

arxiv created 2020/06/25 · arxiv updated 2020/06/26

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.

Citations

• Residual Dense Network for Image Super-Resolution

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