RIA (version 1.6.1)

glrlm_all: Creates gray-level run length matrix of all possible directions of a RIA image

Description

Creates gray-level run length matrix (GLRLM) from RIA_image. GLRLM assesses the spatial relation of voxels to each other by investigating how many times same value voxels occur next to each other in a given direction. While the glrlm function calculates the GLRLM in one given direction, the glrlm_all function simultaneously calculates all GLRLMs in all possible directions. For 3D datasets, this means GLCMs will be calculated for all 13 different directions. In case of 2D datasets, only 4 are returned by default. By default the use_type is set to discretize, therefore GLRLMs will be calculated for all discretized images in all directions. Also single data processing is supported, then by default the image in the $modif slot will be used. If use_slot is given, then the data present in RIA_image$use_slot will be used for calculations. Results will be saved into the glrlm slot. The name of the subslot is automatically generated by RIA.

Usage

glrlm_all(
  RIA_data_in,
  use_type = "discretized",
  use_orig = FALSE,
  use_slot = NULL,
  save_name = NULL,
  verbose_in = TRUE
)

Value

RIA_image containing the GLRLMs.

Arguments

RIA_data_in

RIA_image.

use_type

string, can be "single" which runs the function on a single image, which is determined using "use_orig" or "use_slot". "discretized" takes all datasets in the RIA_image$discretized slot and runs the analysis on them.

use_orig

logical, indicating to use image present in RIA_data$orig. If FALSE, the modified image will be used stored in RIA_data$modif.

use_slot

string, name of slot where data wished to be used is. Use if the desired image is not in the data$orig or data$modif slot of the RIA_image. For example, if the desired dataset is in RIA_image$discretized$ep_4, then use_slot should be discretized$ep_4. The results are automatically saved. If the results are not saved to the desired slot, then please use save_name parameter.

save_name

string, indicating the name of subslot of $glcm to save results to. If left empty, then it will be automatically determined by RIA.

verbose_in

logical indicating whether to print detailed information. Most prints can also be suppressed using the suppressMessages function.

References

Márton KOLOSSVÁRY et al. Radiomic Features Are Superior to Conventional Quantitative Computed Tomographic Metrics to Identify Coronary Plaques With Napkin-Ring Sign Circulation: Cardiovascular Imaging (2017). DOI: 10.1161/circimaging.117.006843 https://pubmed.ncbi.nlm.nih.gov/29233836/

Márton KOLOSSVÁRY et al. Cardiac Computed Tomography Radiomics: A Comprehensive Review on Radiomic Techniques. Journal of Thoracic Imaging (2018). DOI: 10.1097/RTI.0000000000000268 https://pubmed.ncbi.nlm.nih.gov/28346329/

Examples

if (FALSE) {
#Discretize loaded image and then calculate GLRLM matrix of RIA_image$modif
RIA_image <- discretize(RIA_image, bins_in = c(4, 8), equal_prob = TRUE,
use_orig = TRUE, write_orig = FALSE)
RIA_image <- glrlm_all(RIA_image, use_type = "single")

#Use use_slot parameter to set which image to use
RIA_image <- glrlm_all(RIA_image, use_type = "single",
use_orig = FALSE, use_slot = "discretized$ep_4")

#Batch calculation of GLCM matrices on all disretized images
RIA_image <- glrlm_all(RIA_image)
}