class "Carto3D"
Extract non-stardard elements
Constructor for Latex report
Initialization of the slice numbers
Vertical distribution of the lesion
Compute contraleral normalization values
Carto3D to MRIaggr converter
Image thresholding
Compute descriptive statistics
Compress a MRIaggr object
Compute regional contrast parameters
3D median filtering
Diplay a legend of a contrast map
Interface to the Growing Region algorithm
Compute contralateral normalization
Estimation of the local regularization parameters
Compute spatial groups
Lesion volume displayed by slices
Extract parameters
2D median filtering
Reduce a MRIaggr
parameter initialization
Array to data.frame converter
Potts model simulation
Compute reperfusion and hypoperfusion tables
Compute spatial groups
Allocate a neighbourhood matrix
Write an image file
Image filtration
Extract the dimensions of a voxel
Extract default values
Initialization of a filter
Class "MRIaggr"
Boxplot spatial group characteristics
Array constructor for MRIaggr object
Truncated Normal distribution
Compute normalization values
Growing Region algorithm
Allocate clinical data
Mid-saggital plan search
Checking argument validity
3D filtering
Summary Method for Class "MRIaggr"
data.frame to array converter
Extract clinical data
Find disjoint spatial blocks of sites
Diplay a contrast parameter by coordinates
Extract the identifier
Automatic Growing Region algorithm
Compute geometric caracteristics of a spatial group
Outline a region on a slice
Allocate volumic information
Display initialization
Compute spatial groups
Extract reference values
Set or Query Default Values for MRIaggr
Extract spatial coordinates
Correlation between contrast parameters
Checking of the fMMalgo Graphical display of the probability distribution by group
Allocate the position of the mid-saggital plan
Example of processed MRIaggr object
Allocate normalization values
Display quality criteria for the GR algorithm
Find spatial groups
Extract the data dimension
Compute the neighbourhood matrix
Add the position of the mid-sagittal plan
Initialization of the slice numbers
2D filtering
Allocate new contrast parameters
Spatial regularization
Allocate non standard elements
Assessment of clustering quality
initialisation of the fMMalgo Find spatial groups
Potts model simulation
Spatial regularization using ICM
Find disjoint spatial blocks of sites
Find the mid-sagittal plan
Probabilistic tissue type segmentation
A user frendly interface to fMMalgo
Extract the position of the mid-sagittal plan
finite Mixture Model with spatial regularization
Initialization of a neighbourhood filter
Color initialization
Growing Region initialization
ROC analysis
Extract the position of the lesion in each hemisphere
Read an image file
Computation of the spatial potential
3D plot of the lesion
Initializateurs for the constLatex function
Management, display and processing of cerebral imaging data.
Brain-Background discrimination
Allocate new default values
Pre-processing of the fMMalgo Device management
Outline a region on a slice
Extract a neighbourhood matrix
Graphical display of the mixture distribution
Extract the call of the methods applied on the object
Iterated conditional means for spatial regularization
Extract the normalization values
Computation of the spatial potential
Estimation of the local and regional spatial correlation
Extract the number of observations
Extract contrast parameters
Simulation under the mixture model
Remove an element of ls_descStats
Gaussian kernel
Slice by slice display
Plot the distribution of the contrast parameter
Compute the outline of a spatial group
Extract volumic information
Area under the PR curve
Write an image file
Remove a contrast parameter
Logistic transform
Graphical display of the convergence criteria
Index initialization
Array constructor for Carto3D objects
Euclidean distance to a spatial group
Draw a sample from a Potts model
Estimation of the local regularization parameters