glrlm_stat: GLRLM-based statistics

Description Usage Arguments Value References Examples

View source: R/glrlm_stat.R

Description

Calculates GLRLM-based statistics for given GLRLM matrix.

Usage

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glrlm_stat(RIA_data_in, use_type = "single", use_orig = FALSE,
  use_slot = "glrlm$es_8_111", save_name = NULL, verbose_in = TRUE)

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". "glrlm" takes all datasets in the RIA_image$glrlm 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. However, GLRLM matrices are usually note present in either slots, therefore giving the slot name using use_slot is advised.

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, ig the desired dataset is in RIA_image$glrlm$ep_4, then use_slot should be glrlm$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 $glrlm to save results to. If left empty, then it will be automatically determined.

verbose_in

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

Value

RIA_image containing the statistical information.

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://www.ncbi.nlm.nih.gov/pubmed/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://www.ncbi.nlm.nih.gov/pubmed/28346329

Examples

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## Not run: 
#Discretize loaded image and then calculate GLRLM statistics
RIA_image <- discretize(RIA_image, bins_in = 8, equal_prob = TRUE)
RIA_image <- glrlm(RIA_image, use_orig = FALSE, use_slot = "discretized$ep_8",
right = TRUE, down = TRUE, forward = FALSE)
RIA_image <- glrlm_stat(RIA_image, use_orig = FALSE, use_slot = "glrlm$ep_8_110")

#Batch calculation of GLRLM-based statistics on all calculated GLRLMs
RIA_image <- glrlm_stat(RIA_image, use_type = "discretized")

## End(Not run)

RIA documentation built on July 2, 2018, 1:04 a.m.