first_order: Calculates first-order statistical metrics for RIA_image

Description Usage Arguments Value References Examples

View source: R/first_order.R

Description

Calculates first-order statistical metrics of RIA_image. First-order metrics discard all spatial information. By default the $modif image will be used to calculate statistics. If use_slot is given, then the data present in RIA_image$use_slot will be used for calculations. Results will be saved into the $stat_fo slot. The name of the subslot is determined by the supplied string in $save_name, or is automatically generated by RIA.

Usage

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first_order(RIA_data_in, use_type = "single", use_orig = TRUE,
  use_slot = NULL, 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". "discretized" takes all datasets in the RIA_image$discretized slot and runs the analysis on them.

use_orig

logical, indicating whether 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 $stat_fo 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 suppresed 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: 
#Calculate first-order statistics on original data
RIA_image <- first_order(RIA_image, use_orig = TRUE)

#Dichotomize loaded image and then calculate first order statistics
on it and save results into the RIA_image
RIA_image <- dichotomize(RIA_image, bins_in = c(4, 8), equal_prob = TRUE,
use_orig = TRUE, write_orig = FALSE)
RIA_image <- first_order(RIA_image, use_orig = FALSE, verbose_in = TRUE)

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

#Batch calculation of first-order statistics on all discretized images
RIA_image <- first_order(RIA_image, use_type = "discretized")

## End(Not run)

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