Retinal vessel segmentation by probing adaptive to lighting variations
Abstract
We introduce a novel method to extract the vessels in eye fun-dus images which is adaptive to lighting variations. In the Logarithmic Image Processing framework, a 3-segment probe detects the vessels by probing the topographic surface of an image from below. A map of contrasts between the probe and the image allows to detect the vessels by a threshold. In a lowly contrasted image, results show that our method better extract the vessels than another state-of the-art method. In a highly contrasted image database (DRIVE) with a reference , ours has an accuracy of 0.9454 which is similar or better than three state-of-the-art methods and below three others. The three best methods have a higher accuracy than a manual segmentation by another expert. Importantly, our method automatically adapts to the lighting conditions of the image acquisition.
Cite
@article{arxiv.2004.13992,
title = {Retinal vessel segmentation by probing adaptive to lighting variations},
author = {Guillaume Noyel and Christine Vartin and Peter Boyle and Laurent Kodjikian},
journal= {arXiv preprint arXiv:2004.13992},
year = {2020}
}
Comments
Proceedings of 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI).To appear in https://ieeexplore.ieee.org