Dicom Series Read Modify Write


This example illustrates how to read a DICOM series, modify the 3D image, and then write the result as a DICOM series.

Reading the DICOM series is a three step process: first obtain the series ID, then obtain the file names associated with the series ID, and finally use the series reader to read the images. By default the DICOM meta-data dictionary for each of the slices is not read. In this example we configure the series reader to load the meta-data dictionary including all of the private tags.

Modifying the 3D image can involve changes to its physical characteristics (spacing, direction cosines) and its intensities. In our case we only modify the intensities by blurring the image.

Writing the 3D image as a DICOM series is done by configuring the meta-data dictionary for each of the slices and then writing it in DICOM format. In our case we copy some of the meta-data from the original dictionaries which are available from the series reader. We then set some additional meta-data values to indicate that this series is derived from the original acquired data. Note that we write the intensity values as is and thus do not set the rescale slope (0028|1053), rescale intercept (0028|1052) meta-data dictionary values.

See also Read Image Meta-Data Dictionary and Print, Dicom Series Reader.


import SimpleITK as sitk

import sys
import time
import os

if len(sys.argv) < 3:
        "Usage: python "
        + __file__
        + " <input_directory_with_DICOM_series> <output_directory>"

# Read the original series. First obtain the series file names using the
# image series reader.
data_directory = sys.argv[1]
series_IDs = sitk.ImageSeriesReader.GetGDCMSeriesIDs(data_directory)
if not series_IDs:
        'ERROR: given directory "'
        + data_directory
        + '" does not contain a DICOM series.'
series_file_names = sitk.ImageSeriesReader.GetGDCMSeriesFileNames(
    data_directory, series_IDs[0]

series_reader = sitk.ImageSeriesReader()

# 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.
image3D = series_reader.Execute()

# Modify the image (blurring)
filtered_image = sitk.DiscreteGaussian(image3D)

# 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 operation and requires
#            knowledge 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

writer = sitk.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

# Copy relevant tags from the original meta-data dictionary (private tags are
# also accessible).
tags_to_copy = [
    "0010|0010",  # Patient Name
    "0010|0020",  # Patient ID
    "0010|0030",  # Patient Birth Date
    "0020|000D",  # Study Instance UID, for machine consumption
    "0020|0010",  # Study ID, for human consumption
    "0008|0020",  # Study Date
    "0008|0030",  # Study Time
    "0008|0050",  # Accession Number
    "0008|0060",  # Modality

modification_time = time.strftime("%H%M%S")
modification_date = time.strftime("%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.
# NOTE: DICOM tags represent hexadecimal numbers, so 0020|000D and 0020|000d
#       are equivalent. The ITK/SimpleITK dictionary is string based, so these
#       are two different keys, case sensitive. When read from a DICOM file the
#       hexadecimal string representations are in lower case, so we check for
#       existence and get the value after converting to lower case.
# Tags of interest:
direction = filtered_image.GetDirection()
series_tag_values = [
    (k, series_reader.GetMetaData(0, k.lower()))
    for k in tags_to_copy
    if series_reader.HasMetaDataKey(0, k.lower())
] + [
    ("0008|0031", modification_time),  # Series Time
    ("0008|0021", modification_date),  # Series Date
    ("0008|0008", "DERIVED\\SECONDARY"),  # Image Type
        "1.2.826.0.1.3680043.2.1125." + modification_date + ".1" + modification_time,
    # Series Instance UID
                ),  # Image Orientation (Patient)
        series_reader.GetMetaData(0, "0008|103e")
        if series_reader.HasMetaDataKey(0, "0008|103e")
        else "" + " Processed-SimpleITK",
    ),  # Series Description is an optional tag, so may not exist

for i in range(filtered_image.GetDepth()):
    image_slice = filtered_image[:, :, i]
    # Tags shared by the series.
    for tag, value in series_tag_values:
        image_slice.SetMetaData(tag, value)
    # Slice specific tags.
    #   Instance Creation Date
    image_slice.SetMetaData("0008|0012", time.strftime("%Y%m%d"))
    #   Instance Creation Time
    image_slice.SetMetaData("0008|0013", time.strftime("%H%M%S"))
    #   Image Position (Patient)
        "\\".join(map(str, filtered_image.TransformIndexToPhysicalPoint((0, 0, i)))),
    #   Instance Number
    image_slice.SetMetaData("0020|0013", str(i))

    # Write to the output directory and add the extension dcm, to force writing
    # in DICOM format.
    writer.SetFileName(os.path.join(sys.argv[2], str(i) + ".dcm"))