title: Automatic registration of retina images based on genetic techniques.
abstract: The aim of this paper is to develop an automatic method for the registration of multitemporal digital images of the fundus of the human retina. The images are acquired from the same patient at different times by a color fundus camera. The proposed approach is based on the application of global optimization techniques to previously extracted maps of curvilinear structures in the images to be registered (such structures being represented by the vessels in the human retina): in particular, a genetic algorithm is used, in order to estimate the optimum transformation between the input and the base image. The algorithm is tested on two different types of data, gray scale and color images, and for both types, images with small changes and with large changes are used. The comparison between the registered images using the implemented method and a manual one points out that the proposed algorithm provides an accurate registration. The convergence to a solution is not possible only when dealing with images taken from very different view-points.
authors.affiliation: University of Genoa, Dept. of Biophysical and Electronic Eng. (DIBE), Via Opera Pia 11a, I-16145, Italy. vulcano@dibe.unige.it
authors.forename: G
authors.initials: G
authors.lastname: Troglio
authors.forename: J A
authors.initials: JA
authors.lastname: Benediktsson
authors.forename: S B
authors.initials: SB
authors.lastname: Serpico
authors.forename: G
authors.initials: G
authors.lastname: Moser
authors.forename: R A
authors.initials: RA
authors.lastname: Karlsson
authors.forename: G H
authors.initials: GH
authors.lastname: Halldorsson
authors.forename: E
authors.initials: E
authors.lastname: Stefansson
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003124:Colorimetry / Q000379:methods; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012171:Retinal Vessels / Q000033:anatomy & histology*; D042262:Retinoscopy / Q000379:methods*; D012680:Sensitivity and Specificity; D013382:Subtraction Technique