Registration of retinal images from Public Health by minimising an error between vessels using an affine model with radial distortions - INTERNATIONAL PREVENTION RESEARCH INSTITUTE Access content directly
Conference Poster Year : 2019

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

Abstract

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.
Fichier principal
Vignette du fichier
2019_NoyelOwensBoyle_ISBI_Poster.pdf (5.15 Mo) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-02099855 , version 1 (15-04-2019)

Licence

Copyright

Identifiers

  • HAL Id : hal-02099855 , version 1

Cite

Guillaume Noyel, Rebecca Thomas, Simon Iles, Gavin Bhakta, Andrew Crowder, et al.. Registration of retinal images from Public Health by minimising an error between vessels using an affine model with radial distortions. IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019), Apr 2019, Venice, Italy. , 2019. ⟨hal-02099855⟩

Relations

74 View
34 Download

Share

Gmail Facebook X LinkedIn More