Functions to extract first and second order statistics from images.

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)

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")`

)

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 tumorglcm(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"

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))`

:

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))

- Fixes for
`R CMD check --as-cran`

- Fixed the vignette for this version to pass.

- Numerous bugfixes/edge cases
- Better handling of NAs in matrices
- Minor optimizations

- Added generator functions for classes
- Added option to glrlm, glszm and mglszm truncate output matrix
- Changed algorithm used to calculate glcm, resulting in speed increases for larger images

- First release!