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MRIaggr (version 1.1.3)

Management, Display, and Processing of Medical Imaging Data

Description

Provide a compact storage for medical imaging data with access and display possibilities. Basic tools for processing brain imaging data are proposed like extraction of brain voxels, morphological image segmentation, and filtering / normalization of contrast parameters. Specific tools are also provided for blood perfusion imaging to calculate hypoperfusion and reperfusion volumes.

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Version

Install

install.packages('MRIaggr')

Monthly Downloads

34

Version

1.1.3

License

GPL-3

Maintainer

Brice Ozenne

Last Published

November 2nd, 2015

Functions in MRIaggr (1.1.3)

Extract the position of the mid-sagittal plan

Boxplot spatial group characteristics

Initialization of the slice numbers

Extract the data dimension

Class "MRIaggr"

allocHemisphere

Allocate the position of the mid-saggital plan

MRIaggr.Pat1_red

Example of processed MRIaggr object

Correlation between contrast parameters

calcGroupsCoords

Compute spatial groups

Growing Region initialization

calcDistTissues

Compute descriptive statistics

Automatic Growing Region algorithm

Brain-Background discrimination

filtrage3Dmed_cpp

3D median filtering

Constructor for Latex report

Spatial regularization

data.frame to array converter

calcRegionalContrast

Compute regional contrast parameters

Allocate a neighbourhood matrix

class "Carto3D"

Probabilistic tissue type segmentation

Array to data.frame converter

Initialization of the slice numbers

selectHemispheres

Extract the position of the lesion in each hemisphere

Write an image file

Assessment of clustering quality

Extract the number of observations

Set or Query Default Values for MRIaggr

MRIaggr-package

Management, display and processing of cerebral imaging data.

calcGroupsW_cpp

Find spatial groups

Logistic transform

calcROCthreshold

Carto3D2MRIaggr

Carto3D to MRIaggr converter

Array constructor for Carto3D objects

Allocate volumic information

Area under the PR curve

Extract clinical data

Potts model simulation

Diplay a contrast parameter by coordinates

selectDescStats

Extract non-stardard elements

plotTableLesion

Lesion volume displayed by slices

Extract the call of the methods applied on the object

Display quality criteria for the GR algorithm

Interface to the Growing Region algorithm

Read an image file

Image filtration

Pre-processing of the fMMalgo arguments

calcGroupsCoords_cpp

Find spatial groups

calcContralateral

Compute contraleral normalization values

Compute spatial groups

Find disjoint spatial blocks of sites

Find disjoint spatial blocks of sites

Allocate non standard elements

Compute the neighbourhood matrix

initNeighborhood

Initialization of a neighbourhood filter

initDisplayWindow

Device management

Outline a region on a slice

initialisation of the fMMalgo algorithm

selectDefault_value

Extract reference values

calcPottsParameter

Estimation of the local regularization parameters

Allocate new contrast parameters

Growing Region algorithm

Euclidean distance to a spatial group

Compute spatial groups

Extract volumic information

summary-methods

Summary Method for Class "MRIaggr"

constCompressMRIaggr

Compress a MRIaggr object

constReduceMRIaggr

Reduce a MRIaggr

calcTableHypoReperf

Compute reperfusion and hypoperfusion tables

pointsHemisphere

Add the position of the mid-sagittal plan

Image thresholding

Initializateurs for the constLatex function

Mid-saggital plan search

Initialization of a filter

Checking of the fMMalgo arguments

filtrage2Dmed_cpp

2D median filtering

3D plot of the lesion

Remove a contrast parameter

Display initialization

Extract a neighbourhood matrix

Draw a sample from a Potts model

simulPottsFast_cpp

Potts model simulation

Extract the dimensions of a voxel

Extract spatial coordinates

Remove an element of ls_descStats

Write an image file

Compute geometric caracteristics of a spatial group

selectParameter

Extract parameters

calcMultiPotential_cpp

Computation of the spatial potential

Simulation under the mixture model

Checking argument validity

Gaussian kernel

Graphical display of the probability distribution by group

Estimation of the local regularization parameters

A user frendly interface to fMMalgo

selectOptionsMRIaggr

Extract default values

Spatial regularization using ICM

Graphical display of the convergence criteria

Extract contrast parameters

calcNormalization

Compute normalization values

Plot the distribution of the contrast parameter

Outline a region on a slice

Index initialization

Slice by slice display

Truncated Normal distribution

Graphical display of the mixture distribution

calcMultiPotential

Computation of the spatial potential

Iterated conditional means for spatial regularization

Estimation of the local and regional spatial correlation

Diplay a legend of a contrast map

Compute the outline of a spatial group

allocNormalization

Allocate normalization values

Compute contralateral normalization

Find the mid-sagittal plan

Color initialization

Allocate clinical data

Array constructor for MRIaggr object

calcTableLesion

Vertical distribution of the lesion

parameter initialization

selectIdentifier

Extract the identifier

selectNormalization

Extract the normalization values

finite Mixture Model with spatial regularization

allocOptionsMRIaggr

Allocate new default values