mritc
(Package: mritc) :
MRI Tissue Classification Using Various Methods
Conduct the MRI tissue classification using different methods including: the normal mixture model (NMM) fitted by the Expectation-Maximization (EM) algorithm; the hidden Markov normal mixture model (HMNMM) fitted by the Iterated Conditional Mode (ICM) algorithm, the Hidden Markov Random Field EM (HMRFEM) algorithm, or the Bayesian Markov chain Monte Carlo method (MCMC); the partial volume HMNMM fitted by the modified EM (PVHMRFEM) algorithm or the higher resolution HMNMM fitted by the MCMC method (MCMCsub); the HMNMM with both PV and intensity non-uniformity addressed (MCMCsubbias).
● Data Source:
CranContrib
● Keywords: classif
● Alias: mritc, mritc.bayes, mritc.em, mritc.hmrfem, mritc.icm, mritc.pvhmrfem
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0 images
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measureMRI
(Package: mritc) :
Compare the Predicted Classsification Results with the Truth
Calculate and demonstrate different measures for classification results based on the truth.
● Data Source:
CranContrib
● Keywords: utilities
● Alias: measureMRI
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0 images
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mritc-package
(Package: mritc) :
MRI Tissue Classification Package
Use various methods to do MRI tissue classification.
● Data Source:
CranContrib
● Keywords: package
● Alias: mritc-package
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0 images
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readMRI
(Package: mritc) :
Read an MR Image into an Array
Read an MR image of different formats into an array.
● Data Source:
CranContrib
● Keywords: utilities
● Alias: readMRI
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0 images
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print.mritc
(Package: mritc) :
Print Method for Class "mritc"
Print out some information of an object of class "mritc".
● Data Source:
CranContrib
● Keywords: methods
● Alias: print.mritc
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0 images
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rnormmix
(Package: mritc) :
Generate Random Samples from a Normal Mixture Model
Generate random samples from a normal mixture model.
● Data Source:
CranContrib
● Keywords: distribution
● Alias: rnormmix
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0 images
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initNormMix
(Package: mritc) :
Get the Initial Estimate of the Parameters of a Normal Mixture Model
Obtain initial estimation of proportions, means, and standard deviations of different components (tissue types for MRI) based on threshold values generated by Otsu's method implemented by a fast algorithm, or proportion of different components.
● Data Source:
CranContrib
● Keywords: classif
● Alias: initOtsu, initProp
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0 images
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makeMRIspatial
(Package: mritc) :
Obtain Spatial Features of a Mask of an MR Image
Obtain various spatial features of an MR image, which are used in tissue classification.
● Data Source:
CranContrib
● Keywords: spatial
● Alias: makeMRIspatial
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0 images
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writeMRI
(Package: mritc) :
Write an MR Image
Write an MR image into a file of different formats.
● Data Source:
CranContrib
● Keywords: utilities
● Alias: writeMRI
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0 images
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emnormmix
(Package: mritc) :
Estimate the Parameters of a Normal Mixture Model Using the EM Algorithm
Use the EM Algorithm to estimate the parameters of a normal mixture model.
● Data Source:
CranContrib
● Keywords: utilities
● Alias: emnormmix
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0 images
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