oro_compare.Rmd#> Note: code examples will not be evaluated because they depend on local data.Radtools forwards to oro.dicom and oro.nifti under the hood for reading images and extracting data from them. The added value of radtools is to provide simple, uniform functions to access metadata in convenient formats, reducing the need for code duplication or for understanding the finer points of oro.dicom and oro.nifti. In this vignette we compare some of radtools’ functionality for metadata extraction to equivalent code using oro.dicom and oro.nifti.
Load sample data:
dicom_data <- radtools::read_dicom("~/Dropbox/radtools_vignette_data/prostate/")
nifti_data_rad <- radtools::read_nifti1("~/Dropbox/radtools_vignette_data/filtered_func_data.nii.gz")
nifti_data_oro <- oro.nifti::readNIfTI("~/Dropbox/radtools_vignette_data/filtered_func_data.nii.gz")The functions radtools::img_dimensions and radtools::num_slices work for both DICOM and NIfTI images.
radtools::img_dimensions(dicom_data)
radtools::img_dimensions(nifti_data_rad)
radtools::num_slices(dicom_data)
radtools::num_slices(nifti_data_rad)The radtools::header_fields function works for both DICOM and NIfTI data.
fields <- radtools::header_fields(dicom_data)
head(fields, 10)oro.dicom does not contain a direct function for this. You can get the metadata table with oro.dicom::dicomTable and extract its column names. You have to pass dicom_data$hdr instead of dicom_data directly.
tab <- oro.dicom::dicomTable(dicom_data$hdr)
fields <- colnames(tab)
head(fields, 10)All NIfTI datasets have the same metadata attributes.
fields <- radtools::header_fields(nifti_data_rad)
head(fields, 10)oro.nifti does not provide a function to get the names of metadata attributes; accessors for each individual metadata attribute are provided.
Both radtools and oro.dicom provide functions to get the values of a metadata attribute across slices by the attribute name.
radtools::header_value(dicom_data, "SliceLocation")In oro.dicom, you have to pass dicom_data$hdr instead of dicom_data directly.
oro.dicom::extractHeader(dicom_data$hdr, "SliceLocation")Both radtools and oro.dicom provide functions to extract all metadata as a matrix. See below for the different matrix formats.
mat <- radtools::dicom_header_as_matrix(dicom_data)
kable(mat[1:10, 1:6])In oro.dicom, you have to pass dicom_data$hdr instead of dicom_data directly. The row names of the matrix are the .dcm file names.
mat <- oro.dicom::dicomTable(dicom_data$hdr)
kable(mat[1:10, 1:6])
nifti_header_vals <- radtools::nifti1_header_values(nifti_data_rad)
head(nifti_header_vals[names(nifti_header_vals) != ".Data"])This functionality is not available in oro.nifti. Accessors are provided for individual metadata attributes.
In DICOM datasets, many attributes have constant values across all slices. These are properties of the data acquisition as a whole, as opposed to individual slices.
Radtools provides a direct function to get these dataset attributes as a named list. Numeric values are returned as numbers by default.
const_attributes <- radtools::dicom_constant_header_values(dicom_data)
head(const_attributes)With oro.dicom, a few lines of code are required to access overall dataset attributes. All attributes are returned as strings.
The radtools::img_data_to_mat function works for both DICOM and NIfTI data.
mat_dicom <- radtools::img_data_to_mat(dicom_data)
dim(mat_dicom)
mat_nifti <- radtools::img_data_to_mat(nifti_data_rad)
dim(mat_nifti)oro.dicom and oro.nifti each have direct functions to get the image data as a matrix. Because of the different typical uses of these formats, the functions have different names.
The radtools::view_slice function works for both DICOM and NIfTI datasets. For datasets with more than three dimensions, data can first be reduced to a 3D matrix with the generic function img_data_to_3D_mat and then radtools::view_slice_mat is agnostic to the original format of the data.
oro.dicom does not provide a direct view function, while oro.nifti does.
radtools::view_slice(dicom_data, slice = 10)
mat <- radtools::img_data_to_3D_mat(nifti_data_rad, coord_extra_dim = 90)
radtools::view_slice_mat(mat, slice = 10)oro.nifti provides a direct image function:
oro.nifti::image(nifti_data_oro, z = 10, w = 90, plot.type = "single")Radtools provides functions to explore the DICOM standard itself.
radtools::dicom_standard_version()
radtools::dicom_standard_web()
radtools::dicom_standard_timestamp()Tags:
tags <- radtools::dicom_all_valid_header_tags()
head(tags, 10)Names:
names <- radtools::dicom_all_valid_header_names()
head(names, 10)Keywords:
keywords <- radtools::dicom_all_valid_header_keywords()
head(keywords, 10)
radtools::dicom_search_header_names("manufacturer")
radtools::dicom_search_header_keywords("manufacturer")This functionality is not provided in oro.dicom.