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