Radiomics: Texture Analysis Matrices
** Not Currently Maintained **
This project is not currently being maintained. While I will do my best to help in a timely fashion, you should not expect a prompt response.

The `radiomics`

package is a set of tools for computing texture matrices and features from images.

The release version of this package (April 2016, v0.1.2) is available from CRAN using:

install.packages ("radiomics" )

Or you can install the development version of the package using:

`devtools`:: install_github ("joelcarlson/radiomics" )
library (radiomics)

Texture Matrices
In the package are functions for calculating four different types of matrices and associated feature sets used to quantify the texture of an image.

These matrices are the:

Grey Level Co-occurrence Matrix
Grey Level Run Length Matrix
Grey Level Size Zone Matrix
Multiple Grey Level Size Zone Matrix
Detailed usage directions for calculating features and matrices can be found in the package vignette (use `browseVignettes(package = "radiomics")`

)

Using the Package
Building Texture Matrices
Texture matrices can be created from 2D images by using the abbreviated and lowercase matrix name as a function call:

`tumor <-` radiomics:: tumor #2D MRI slice of a brain tumor
glcm (tumor)
glrlm (tumor)
glszm (tumor)
mglszm (tumor)

A matrix with the class of the texture matrix type is returned, as shown here using `glcm(tumor, n_grey=4)`

```
#> An object of class "glcm"
#> 1 2 3 4
#> 1 0.1617021277 0.03356974 0.001891253 0.0004728132
#> 2 0.0335697400 0.38345154 0.010638298 0.0014184397
#> 3 0.0018912530 0.01063830 0.301654846 0.0184397163
#> 4 0.0004728132 0.00141844 0.018439716 0.0203309693
```

class (glcm (tumor, n_grey= 4 ))[1 ]
#> [1] "glcm"

Visualizing Texture Matrices
Each matrix type has an associated `image`

function for visualization of the results:

image (glcm (tumor))
image (glrlm (tumor))
image (glszm (tumor))
image (mglszm (tumor))

The `image`

functions make use of the `viridis`

scale, as shown here using `image(glcm(tumor, n_grey=64))`

:

Sample image
Calculating Features
Each matrix type has an associated `calc_features`

function, which returns an object of class `data.frame`

with a single observation for each calculated feature. First order features can also be calculated on 2D matrices.

calc_features (tumor)
calc_features (glcm (tumor))
calc_features (glrlm (tumor))
calc_features (glszm (tumor))
calc_features (mglszm (tumor))