Registration of retinal images from Public Health by minimising an error between vessels using an affine model with radial distortions

• Published in: arXiv.org
• Main Authors: Noyel, Guillaume, Thomas, R, Iles, S, Bhakta, G, Crowder, A, Owens, D, Boyle, P
• Format: Paper Journal Article
• Language: English
• Published: Ithaca Cornell University Library, arXiv.org 17.04.2019
• Subjects: Computer Science - Computer Vision and Pattern Recognition; Error detection; Physics - Medical Physics; Public health; Retinal images; Vessels
• ISSN: 2331-8422
• DOI: 10.48550/arxiv.1904.12733

In order to estimate a registration model of eye fundus images made of an affinity and two radial distortions, we introduce an estimation criterion based on an error between the vessels. In [1], we estimated this model by minimising the error between characteristics points. In this paper, the detected vessels are selected using the circle and ellipse equations of the overlap area boundaries deduced from our model. Our method successfully registers 96 % of the 271 pairs in a Public Health dataset acquired mostly with different cameras. This is better than our previous method [1] and better than three other state-of-the-art methods. On a publicly available dataset, ours still better register the images than the reference method.