postkcluster: Segmentation with a fixed number of clusters

Description Usage Arguments Details Author(s) References See Also Examples

View source: R/postkcluster.R

Description

postkcluster re-clusters the data with a user-specified number of components, and displays the segmented image.

Usage

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postkcluster(mask, cx, clk=4, plot=TRUE)

Arguments

mask

masked full-sized image data prepared by premask

cx

data segmentation prepared by postdataseg

clk

desired fixed number of components, including the background component, to use in the data segmentation; default clk=4: gray matter (GM), white matter (WM), CSF, and background

plot

logical variable; enables suspension of output images (default = TRUE)

Details

Partitioning clustering around medoids (PAM) is applied to the classes simulated from dpmixsim as a post-processing step. This procedure may be applied to merge clusters, and reduce the number of clusters to the specified value clk. postkcluster computes a clara object using cluster (see Struyf et.al.), a list representing a clustering of the data into clk clusters.

Author(s)

Adelino Ferreira da Silva, Universidade Nova de Lisboa, Faculdade de Ciencias e Tecnologia, Portugal, [email protected].

References

Adelino Ferreira da Silva, A Dirichlet process mixture model for brain MRI tissue classification, Medical Image Analysis 11 (2007) 169-182.

Adelino Ferreira da Silva, Bayesian mixture models of variable dimension for image segmentation, Comput. Methods Programs Biomed. 94 (2009) 1-14.

Anja Struyf, Mia Hubert & Peter J. Rousseeuw (1996): Clustering in an Object-Oriented Environment. Journal of Statistical Software, 1. http://www.stat.ucla.edu/journals/jss/

See Also

dpmixsim, readsliceimg, premask, postdpmixciz, postdataseg, postimgcomps

Examples

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## Not run: 
## see Examples in `dpmixsim'.

## End(Not run)

dpmixsim documentation built on May 29, 2017, 11:04 p.m.