load_nifti: Loads NIfTI images to RIA image format
In neuroconductor/RIA: Radiomics Image Analysis Toolbox for Medial Images

Description Usage Arguments Details Value References Examples

Loads NIfTI images to a RIA_image object. RIA_image is a list with three mandatory attributes.

RIA_data is a RIA_data object, which has two potential slots. $orig contains the original image after loading $modif contains the image that has been modified using functions.
RIA_header is a RIA_header object, which is list of header information.
RIA_log is a RIA_log object, which is a list updated by RIA functions and acts as a log and possible input for some functions.

Further attributes may also be added by RIA functions.

load_nifti(filename, image_dim = 3, mask_filename = NULL,
  keep_mask_values = 1, switch_z = TRUE, crop_in = TRUE,
  replace_in = TRUE, center_in = FALSE, zero_value = NULL,
  min_to = -1024, verbose_in = TRUE, reorient_in = TRUE, ...)

`filename`	string, file path to directory containing NIfTI file.
`image_dim`	integer, dimensions of the image.
`mask_filename`	string, file path to optional directory containing NIfTI file of mask image.
`keep_mask_values`	integer vector, indicates which value or values of the mask image to use as indicator to identify voxels wished to be processed. Usually 1-s indicate voxels wished to be processed. However, one mask image might contain several segmentations, in which case supplying several integers is allowed. Furthermore, if the same string is supplyied to filename and mask_filename, then the integers in keep_mask_values are used to specify which voxel values to analyze. This way the provided image can be segmented to specific compontents. For example, if you wish to analyze only the low-density non-calcified component of coronary plaques, then keep_mask_values can specify this by setting it to: -100:30
`switch_z`	logical, indicating whether to change the orientation of the images in the Z axis. Some software reverse the order of the manipulated image in the Z axis, and therefore the images of the mask image need to be reveresed.
`crop_in`	logical, indicating whether to crop RIA_image to smallest bounding box.
`replace_in`	logical, whether to replace smallest values indicated by zero_value, which are considered to indicate no signal, to NA.
`center_in`	logical, whether to shift data so smallest value is equal to min_to input parameter.
`zero_value`	integer, indicating voxels values which are considered not to have any information. If left empty, then the smallest HU value in the image will be used, if replace_in is TRUE.
`min_to`	integer, value to which data is shifted to if center_in is TRUE.
`verbose_in`	logical, indicating whether to print detailed information. Most prints can also be suppresed using the `suppressMessages` function.
`reorient_in`	reorient parameter input of `readNIfTI`.
`...`	additional arguments to `readNIfTI`, `nifti_header`.

load_nifti is used to transform NIfTI datasets into the RIA environment. RIA_image object was developed to facilitate and simplify radiomics calculations by keeping all necessary information in one place.

RIA_data stores the image that is converted to numerical 3D arrays using readNIfTI. The function stores the original loaded image in RIA_data$orig, while all modified images are stored in RIA_data$modif. By default, the original image RIA_data$orig is untouched by functions other than those operating in load_nifti. While other functions operate on the RIA_data$modif image by default.
Due to memory concerns, there can only be one RIA_data$orig and RIA_data$modif image present at one time in a RIA_image. Therefore, if image manipulations are performed, then the RIA_data$modif will be overwritten. However, functions can save images into new slots of RIA_image, for example the discretize function can save discretized images to the discretized slot of RIA_image.
load_nifti not only loads the image based on parameters that can be set for readNIfTI, but also can perform minimal manipulations on the image itself.
crop_in logical variable is used to indicate, whether to crop the image to the smallest bounding box still containing all the information. If TRUE, then all X, Y and potentially Z slices containing no information will be removed. This allows significant reduction of necessary memory to store image data.
zero_value parameter is used to indicate HU values which contain no information. If left empty, then the smallest value will be considered as indicating voxels without a signal.
replace_in logical can be used to change values that are considered to have no signal to NA. This is necessary to receive proper statistical values later on.
center_in logical is used to indicate whether the values should be shifted. Some vendors save HU values as positive integers to spare memory and minimalize file sizes. Therefore, in some instances shift of the scale is needed. By default, the values are shifted by -1024, but in other cases a different constant might be required, which can be set using the min_to input.

RIA_header is a list containing the most basic patient and examination information present in the NIfTI file.

RIA_log is a list of variables, which give an overview of what has been done with the image. If the whole RIA_image is supplied to a function, the information regarding the manipulations are written into the $events array in chronological order. Furthermore, some additional information is also saved in the log, which might be needed for further analysis.

Returns a RIA_image object. RIA_image is a list with three mandatory attributes.

RIA_data is a RIA_data object containing the image in $orig slot.
RIA_header is a RIA_header object, which is s list of meta information.
RIA_log is a RIA_log object, which is a list updated by RIA functions and acts as a log and possible input for some functions.

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: 
 #Image will be croped to smallest bounding box, and smallest values will be changed to NA,
 while 1024 will be substracted from all other data points.
 RIA_image <- load_nifti("C:/Users/Test/Documents/Radiomics/John_Smith/NIfTI_folder/sample.nii")
 
## End(Not run)