Delibasis, KKAsvestas, PAMatsopoulos, GKIn this paper, an automatic method for determining pairs of corresponding points between medical images is proposed. The method is based on the implementation of an artificial immune system (AIS). AIS is a relatively novel, population based category of algorithms, inspired by theoretical immunologic models. When used as function optimizers, AIS have the attractive property of locating the global optimum of a function as well as a large number of strong local optimum points. In this work, AIS has been applied both for the extraction of an optimal set of candidate points on the reference image and the definition of their corresponding ones on the second image. The performance of the proposed AIS algorithm is evaluated against the widely used Iterative Closest Point (ICP) algorithm in terms of the accuracy of the obtained correspondences and in terms of the accuracy of the point-based registration by the two correspondence algorithms and the Mutual Information criterion, as an intensity-based registration method. Qualitative and quantitative results involving 92 X-ray dental and 10 retinal image pairs subject to known and unknown transformations are presented. The results indicate a superior performance of the proposed AIS algorithm with respect to the ICP algorithm and the Mutual Information, in terms of both correct correspondence and registration accuracy. (C) 2010 Elsevier Ltd. All rights reserved.http://hdl.handle.net/123456789/210101350895-6111ISI:000287561700004413110.1016/j.compmedimag.2010.09.002engPERGAMON-ELSEVIER SCIENCE LTDComputerized Medical Imaging and GraphicsPoint correspondenceImage EnhancementHumansMutual InformationPoint extractionaccuracyX rayOptimizationImmunologyretina imageMedical image registrationtooth radiographypriority journalRadiographic Image Interpretation, Computer-AssistedalgorithmIterative Closest PointImage registrationMedical imagingIterative Closest Pointscorrespondence analysisArtificial Immune SystemimagingArtificial immune systemarticleMutual informationsAlgorithmsperformanceregistrationToothmethodologyartificial immune systemAutomatic point correspondence using an artificial immune system optimization technique for medical image registrationjournalArticle2011Ραδιολογία, Πυρηνική ιατρική και ΑπεικονιστικήRadiology, Nuclear Medicine and Imagingisi - Radiology, Nuclear Medicine & Medical Imaging covers resources on radiation research in biology and biophysics. Resources in this category focus on interventional radiology, investigative radiology, neuroradiology, radiotherapy, and oncology. Nuclear Medicine resources are concerned with the diagnostic, therapeutic, and investigative use of radionuclides. Medical Imaging resources are concerned with computerized medical imaging and graphics.Δημοσίευση σε περιοδικόPublication in journalΕπιστημονικό άρθροScientific articleΕθνικό Μετσόβιο ΠολυτεχνείοGreek Aggregator OpenArchives.gr | National Documentation Centre (EKT)other