Module ITKClassifiers

Collaboration diagram for Module ITKClassifiers:

Classes
class	itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >
class	itk::BayesianClassifierInitializationImageFilter< TInputImage, TProbabilityPrecisionType >
class	itk::ClassifierBase< TDataContainer >
class	itk::ImageClassifierBase< TInputImage, TClassifiedImage >
class	itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >
class	itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >
class	itk::ImageModelEstimatorBase< TInputImage, TMembershipFunction >
class	itk::ScalarImageKmeansImageFilter< TInputImage, TOutputImage >

Detailed Description

This module contains algorithms to classify pixels in an image. It can be used, for example, to identify pixel membership within a set of tissue types. Different algorithms are available including Bayesian classification, Gaussian models, and K-means clustering. After tissue labels have been assigned, they can be modified and applied with the Module ITKLabelMap.

Dependencies:

• Module ITKConnectedComponents
• Module ITKImageGrid
• Module ITKStatistics