A multimodal registration algorithm of eye fundus images using vessels detection and Hough transform.
Image registration is a real challenge because physicians handle many images. Temporal registration is necessary in order to follow the various steps of a disease, whereas multimodal registration allows us to improve the identification of some lesions or to compare pieces of information gathered from different sources. This paper presents an algorithm for temporal and/or multimodal registration of retinal images based on point correspondence. As an example, the algorithm has been applied to the registration of fluorescein images (obtained after a fluorescein dye injection) with green images (green filter of a color image). The vascular tree is first detected in each type of images and bifurcation points are labeled with surrounding vessel orientations. An angle-based invariant is then computed in order to give a probability for two points to match. Then a Bayesian Hough transform is used to sort the transformations with their respective likelihoods. A precise affine estimate is finally computed for most likely transformations. The best transformation is chosen for registration.
Centre de Morphologie Mathématique, Ecole des Mines de Paris, Fontainebleau, France.
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F
Zana
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JC
Klein
D000465:Algorithms; D001499:Bayes Theorem; D003930:Diabetic Retinopathy / Q000175:diagnosis; D005451:Fluorescein Angiography / Q000379:methods / Q000706:statistics & numerical data; D005654:Fundus Oculi; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000295:instrumentation / Q000379:methods* / Q000706:statistics & numerical data; D012171:Retinal Vessels / Q000033:anatomy & histology*; D013997:Time Factors