geometry: Calculates geometry-based parameters of RIA image
In neuroconductor/RIA: Radiomics Image Analysis Toolbox for Medial Images

Description Usage Arguments Value References Examples

Calculates geometry-based parameters of original or subcomponents of an image after discretization. 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_geometry slot. The name of the subslot is determined by the supplied string in save_name, or is automatically generated by RIA.

geometry(RIA_data_in, xy_dim = RIA_data_in$log$orig_xy_dim,
  z_dim = RIA_data_in$log$orig_z_dim,
  all_vol = RIA_data_in$log$orig_vol_mm,
  all_surf = RIA_data_in$log$orig_surf_mm, calc_dist = FALSE,
  calc_sub = TRUE, use_type = "single", use_orig = FALSE,
  use_slot = NULL, save_name = NULL, verbose_in = TRUE)

`RIA_data_in`	RIA_image.
`xy_dim`	numeric, in plane resolution.
`z_dim`	numeric, cross plane resolution.
`all_vol`	numeric, volume of whole lesion.
`all_surf`	numeric, surface of whole lesion.
`calc_dist`	logical, whether to calculate distances, may take very long.
`calc_sub`	logical, indicating whether to calculate metrics for all different values present in the image. This can be useful for calculating metrics of subcomponents for a discretized image. If FALSE, then all voxels are treated equally and the results will be based on the whole 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$discretized slot and runs the analysis on them.
`use_orig`	logical, indicating to use image present in RIA_data$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_geometry to save results to. If left empty, then it will be automatically determined by RIA.
`verbose_in`	logical indicating whether to print detailed information. Most prints can also be suppressed using the `suppressMessages` function.

RIA_image containing geometry calculations.

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

## Not run: 
#Calculate geometry-based parameters on original image
RIA_image <- geometry(RIA_image, use_orig = TRUE, calc_sub = FALSE)

#Discretize loaded image and then calculate geometry-based statistics on subcomponents
RIA_image <- discretize(RIA_image, bins_in = c(4,8), equal_prob = TRUE, use_orig = TRUE)
RIA_image <- geometry(RIA_image, use_orig = FALSE, calc_sub = TRUE)

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

#Batch calculation of geometry-based statistics on all discretized images and subcomponents
RIA_image <- geometry(RIA_image, use_type = "discretized", calc_sub = TRUE)

## End(Not run)