Description Usage Arguments Value References Examples
View source: R/radiomics_all.R
Calculates specified radiomic statistics on RIA_image. Parameters of radiomic functions may be set. By default the the images are discretized to 8, 16 and 32 bins using equally sized and probable binning. Firstorder statistics are calculated on the original image and if asked then on all discretizations. Symmetric GLCMs are calculated for all directions at a distance of 1 for all discretizations. GLRLMs are also calculated for all discretizations. Geometrybased statistics are calculated for the original image as well as all discretizations is requested.
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RIA_data_in 
RIA_image. 
bins_in 
integer vector, number of bins specified. 
equal_prob 
logical or string, indicating to cut data into bins with equal relative frequencies. If FALSE, then equal interval bins will be used. If "both" is supplied, the both equally probable and equal interval bins will be created. 
fo_discretized 
logical, indicating whether to calculate firstorder statistics on discretized images. 
distance 
integer, distance between the voxels being compared. 
statistic 
string, defining the statistic to be calculated on the array of GLCM statistics. By default, statistic is set to "mean", however any function may be provided. The proper syntax is: function(X, attributes). The supplied string must contain a "X", which will be replaced with the array of the GLCM statistics value. Further attributes of the function may also be given. For example, if you wish to calculate the median of all GLCMs calculated in different directions, then it must be supplied as: median(X, na.rm = TRUE). 
geometry_discretized 
logical, indicating whether to calculate geometrybased statistics on discretized images. 
verbose_in 
logical, indicating whether to print detailed information.
Most prints can also be suppressed using the 
RIA_image containing the statistical information.
Márton KOLOSSVÁRY et al. Radiomic Features Are Superior to Conventional Quantitative Computed Tomographic Metrics to Identify Coronary Plaques With NapkinRing 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/
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#Discretize loaded image and then calculate all radiomic statistics
DICOM < radiomics_all(DICOM, equal_prob = "both", bins_in= c(32,64), distance = c(1:2))
## End(Not run)

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