Package gov.nih.mipav.model.algorithms.registration
package gov.nih.mipav.model.algorithms.registration
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ClassesClassDescriptionThis is an automatic registration method based on FLIRT.This is an automatic registration method based on FLIRT.Algorithm for non-linear registration with the DEMONS algorithmThis is a common base class which provides common methods and data members for all BSpline based registration.Data structure which contains the parameters or options used to perform a BSpline based registration of two images.BSpline based registration of 2.5D images.BSpline based registration of 2D images.BSpline registration of 3D images.AlgorithmRegChamfer First slice is template (base image) to which match image is registered.This is an automatic registration method based on FLIRT.This is an automatic registration method based on FLIRT.This is an automatic registration method based on FLIRT.This is an automatic registration method based on FLIRT."Least-Squares Fitting of 2 3-D Point Sets", K.This is an automatic registration method based on FLIRT.This is an automatic registration method based on FLIRT.This is an automatic registration method based on FLIRT.This is an automatic registration method based on FLIRT.Use origin and image orientations to align images based on patient position.Uses a selected
RegistrationMeasureand the user-specified points to output the relevant measure back to the user.AlgorithmRegVOILandmark First slice is template (base image) to which subsequent slices are registered.This class is used to register a 2D source image to a 2D target image.This class is used to register a 3D source image to a 3D target image.This is a common base class for all BSpline-based registrations.This algorithm handles registration algorithms of images with the Demons algorithm and a simple multiscale technique (Demons variant from Tom Vercauteren's 2009 paper, "Diffeomorphic demons: Efficient non-parametric image registration by Tom Vercauteren, Xavier Pennec, Aymeric Perchant, and Nicholas Ayache, NeuroImage, 45, 2009, S61-S72.)Helper class to make it easy to store the necessary information about a minimum.This is an abstract class used to compute the measure of registration between the specified target image and a registered source image.Concrete implementation of the RegistrationMeasure class based on the correlation ratio computed as follows:Concrete implementation of the RegistrationMeasure class based on sum of the squared differences between the target image and the registered source image.Concrete implementation of the RegistrationMeasure class based on the normalized mutual information computed as follows: