RIA (version 1.6.1)

glrlm: Creates gray-level run length matrix from 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. By default the $modif image will be used to calculate GLRLMs. If use_slot is given, then the data present in RIA_image$use_slot will be used for calculations. Results will be saved into the glrlm slot. The name of the subslot is determined by the supplied string in save_name, or is automatically generated by RIA. off_right, off_down and off_z logicals are used to indicate the direction of the runs.

Usage

glrlm(
  RIA_data_in,
  off_right = 1,
  off_down = 0,
  off_z = 0,
  use_type = "single",
  use_orig = FALSE,
  use_slot = NULL,
  save_name = NULL,
  verbose_in = TRUE
)

Value

RIA_image containing the GLRLM.

Arguments

RIA_data_in

RIA_image.

off_right

integer, positive values indicate to look to the right, negative values indicate to look to the left, while 0 indicates no offset in the X plane.

off_down

integer, positive values indicate to look to the right, negative values indicate to look to the left, while 0 indicates no offset in the Y plane.

off_z

integer, positive values indicate to look to the right, negative values indicate to look to the left, while 0 indicates no offset in the Z plane.

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 $glcm to save results to. If left empty, then it will be automatically determined based on the last entry of RIA_image$log$events.

verbose_in

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

References

Mary M. Galloway et al. Texture analysis using gray level run lengths. Computer Graphics and Image Processing. 1975; 4:172-179. DOI: 10.1016/S0146-664X(75)80008-6 https://www.sciencedirect.com/science/article/pii/S0146664X75800086/

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(RIA_image, use_orig = FALSE, verbose_in = TRUE)

#Use use_slot parameter to set which image to use
RIA_image <- glrlm(RIA_image, use_orig = FALSE, use_slot = "discretized$ep_4",
off_right = 1, off_down = 1, off_z = 0)

#Batch calculation of GLRLM matrices on all discretized images
RIA_image <- glrlm(RIA_image, use_type = "discretized",
off_right = 1, off_down = 1, off_z = 0)
}