R package dpmixsim: Dirichlet Process Mixture model simulation for clustering and image segmentation. The package implements a Dirichlet Process Mixture (DPM) model for clustering and image segmentation. The DPM model is a Bayesian nonparametric methodology that relies on MCMC simulations for exploring mixture models with an unknown number of components. The code implements conjugate models with normal structure (conjugate normal-normal DP mixture model). The package’s applications are oriented towards the classification of magnetic resonance images according to tissue type or region of interest.
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References in zbMATH (referenced in 3 articles )
Showing results 1 to 3 of 3.
- Mair, Patrick: Modern psychometrics with R (2018)
- Richard Beare; Bradley Lowekamp; Ziv Yaniv: Image Segmentation, Registration and Characterization in R with SimpleITK (2018) not zbMATH
- Brandon Whitcher; Volker Schmid; Andrew Thorton: Working with the DICOM and NIfTI Data Standards in R (2011) not zbMATH