SimpleITK  1.2.4
DicomSeriesFromArray/DicomSeriesFromArray.R
#=========================================================================
#
# Copyright Insight Software Consortium
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0.txt
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
#=========================================================================
# Run with:
#
# Rscript --vanilla DicomSeriesFromArray.R output_directory
#
library(SimpleITK)
args <- commandArgs( TRUE )
if (length(args) < 1) {
stop("1 argument expected - output_directory")
}
writeSlices <- function(series_tag_values, new_img, i) {
image_slice <- new_img[1:new_img$GetWidth(), 1:new_img$GetHeight(), i]
# Tags shared by the series.
lapply(1:nrow(series_tag_values),
function(tag_index){image_slice$SetMetaData(series_tag_values[tag_index, 1], series_tag_values[tag_index, 2])})
# Slice specific tags.
image_slice$SetMetaData("0008|0012", format(Sys.time(), "%H%M%S")) # Instance Creation Date
image_slice$SetMetaData("0008|0013", format(Sys.time(), "%Y%m%d")) # Instance Creation Time
# Setting the type to CT preserves the slice location.
image_slice$SetMetaData("0008|0060", "CT") # set the type to CT so the thickness is carried over
# (0020, 0032) image position patient determines the 3D spacing between slices.
image_slice$SetMetaData("0020|0032", paste(new_img$TransformIndexToPhysicalPoint(c(0,0,i)), collapse='\\')) # Image Position (Patient)
image_slice$SetMetaData("0020,0013", i-1) # Instance Number
# Write to the output directory and add the extension dcm, to force writing in DICOM format.
writer$SetFileName(file.path(args[[1]], paste(i-1, '.dcm', sep="")))
writer$Execute(image_slice)
}
# Create a new series from an array
new_arr <- array(sample(-10:10, 60, replace=T), dim=c(5, 4, 3))
new_img <- as.image(new_arr)
new_img$SetSpacing(c(2.5,3.5,4.5))
# Write the 3D image as a series
# IMPORTANT: There are many DICOM tags that need to be updated when you modify an
# original image. This is a delicate opration and requires knowlege of
# the DICOM standard. This example only modifies some. For a more complete
# list of tags that need to be modified see:
# http://gdcm.sourceforge.net/wiki/index.php/Writing_DICOM
# If it is critical for your work to generate valid DICOM files,
# It is recommended to use David Clunie's Dicom3tools to validate the files
# (http://www.dclunie.com/dicom3tools.html).
writer <- ImageFileWriter()
# Use the study/series/frame of reference information given in the meta-data
# dictionary and not the automatically generated information from the file IO
writer$KeepOriginalImageUIDOn()
modification_time <- format(Sys.time(), "%H%M%S")
modification_date <- format(Sys.time(), "%Y%m%d")
# Copy some of the tags and add the relevant tags indicating the change.
# For the series instance UID (0020|000e), each of the components is a number, cannot start
# with zero, and separated by a '.' We create a unique series ID using the date and time.
# tags of interest:
direction <- new_img$GetDirection()
series_tag_values = matrix(c("0008|0031",modification_time, # Series Time
"0008|0021",modification_date, # Series Date
"0008|0008","DERIVED\\SECONDARY", # Image Type
"0020|000e", paste("1.2.826.0.1.3680043.2.1125.",modification_date,".1",modification_time, sep=''), # Series Instance UID
"0020|0037", paste(direction[[1]], direction[[4]], direction[[7]],# Image Orientation (Patient)
direction[[2]],direction[[5]],direction[[8]], sep='\\'),
"0008|103e", "Created-SimpleITK"), nrow=6, ncol=2, byrow=TRUE) # Series Description
# Write slices to output directory
invisible(lapply(1:(new_img$GetDepth()), function(i){writeSlices(series_tag_values, new_img, i)}))
# Re-read the series
# Read the original series. First obtain the series file names using the
# image series reader.
data_directory <- args[[1]]
series_IDs <- ImageSeriesReader_GetGDCMSeriesIDs(data_directory)
if (length(series_IDs)==0) {
stop("ERROR: given directory \"", data_directory, "\" does not contain a DICOM series.")
}
series_file_names <- ImageSeriesReader_GetGDCMSeriesFileNames(data_directory, series_IDs[[1]])
series_reader <- ImageSeriesReader()
series_reader$SetFileNames(series_file_names)
# Configure the reader to load all of the DICOM tags (public+private):
# By default tags are not loaded (saves time).
# By default if tags are loaded, the private tags are not loaded.
# We explicitly configure the reader to load tags, including the
# private ones.
series_reader$LoadPrivateTagsOn()
image3D <- series_reader$Execute()
cat(image3D$GetSpacing(),'vs',new_img$GetSpacing(),'\n')