discretize: Discretizes RIA image to a given number of bins

In neuroconductor/RIA: Radiomics Image Analysis Toolbox for Medial Images

Description

Discretizes RIA_image into bins_in number of bins. The equal_prob parameter is used to indicate whether to create bins containing the same number of values. If FALSE then equal sized bins will be created. discretized images will be saved into the $data$modif slot of RIA_image as well as the discretized slot of RIA_image. The name will be automatically created based on the type of dichotomization (ep: equal probability; es: equal size) and the number of bins specified, for example: $dicotomized$es_8 will store the discretized image after equal sized dichotomization into 8 bins. This way many different discretized images using different bin numbers can be saved to the same object for further analysis. The RIA_log will be updated with cut points.

Usage

discretize(RIA_data_in, bins_in = 8, equal_prob = FALSE,
  use_orig = TRUE, write_orig = FALSE, verbose_in = TRUE)

Arguments

RIA_data_in	RIA_image.
bins_in	integer vector, number of bins specified.
equal_prob	logical, indicating to cut data into bins with equal relative frequencies. If FALSE, then equal interval bins will be used.
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.
write_orig	logical, indicating to write cropped image to RIA_data$orig. If FALSE, the modified image will be used stored in RIA_data$modif.
verbose_in	logical, indicating whether to print detailed information. Most prints can also be suppressed using the suppressMessages function.

Value

RIA_image with values discretized to bin values.

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

## Not run: 
#Discretize into 8 bins, each containing equal number of elements
RIA_image <- discretize(RIA_image, bins_in = 8, equal_prob = TRUE,
 use_orig = TRUE, write_orig = FALSE)

#Discretize into 6 bins, each with the same width
RIA_image <- discretize(RIA_image, bins_in = 6, equal_prob = FALSE,
 use_orig = TRUE, write_orig = FALSE)

#Discretize into 2,4,8,16,32 bins, each containing equal number of elements
RIA_image <- discretize(RIA_image, bins_in = 2^(1:5), equal_prob = FALSE,
 use_orig = TRUE, write_orig = FALSE)
 
#D

## End(Not run)

neuroconductor/RIA documentation built on May 21, 2021, 6:56 a.m.