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.
- Publication:
-
arXiv e-prints
- Pub Date:
- April 2020
- DOI:
- 10.48550/arXiv.2004.13992
- arXiv:
- arXiv:2004.13992
- Bibcode:
- 2020arXiv200413992N
- Keywords:
-
- Computer Science - Computer Vision and Pattern Recognition;
- Electrical Engineering and Systems Science - Signal Processing;
- Mathematics - Numerical Analysis;
- Physics - Medical Physics
- E-Print:
- Proceedings of 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI).To appear in https://ieeexplore.ieee.org