The acquisition of high-resolution retinal fundus images with a large field of view (FOV) is challenging due to technological, physiological and economic reasons. This paper proposes a fully automatic framework to reconstruct retinal images of high spatial resolution and increased FOV from multiple low-resolution images captured with non-mydriatic, mobile and video-capable but low-cost cameras. Within the scope of one examination, we scan different regions on the retina by exploiting eye motion conducted by a patient guidance. Appropriate views for our mosaicing method are selected based on optic disk tracking to trace eye movements. For each view, one super-resolved image is reconstructed by fusion of multiple video frames. Finally, all super-resolved views are registered to a common reference using a novel polynomial registration scheme and combined by means of image mosaicing. We evaluated our framework for a mobile and low-cost video fundus camera. In our experiments, we reconstructed retinal images of up to 30{\deg} FOV from 10 complementary views of 15{\deg} FOV. An evaluation of the mosaics by human experts as well as a quantitative comparison to conventional color fundus images encourage the clinical usability of our framework.
@article{arxiv.1602.03458,
title = {Super-Resolved Retinal Image Mosaicing},
author = {Thomas Köhler and Axel Heinrich and Andreas Maier and Joachim Hornegger and Ralf P. Tornow},
journal= {arXiv preprint arXiv:1602.03458},
year = {2016}
}
Comments
accepted for 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI 2016)