Read dicom image information

dcm_information.py

import numpy as np
import pydicom
import matplotlib.pyplot as plt
from pydicom.data import get_testdata_files

print(__doc__)


def get_database(filename, indent=0):
    """Go through all items in the dataset and print them with custom format
    Modelled after Dataset._pretty_str()
    """
    dont_print = ['Pixel Data', 'File Meta Information Version']

    indent_string = "   " * indent
    next_indent_string = "   " * (indent + 1)

    for data_element in filename:
        if data_element.VR == "SQ":  # a sequence
            print(indent_string, data_element.name)
            for sequence_item in data_element.value:
                get_database(sequence_item, indent + 1)
                print(next_indent_string + "---------")
        else:
            if data_element.name in dont_print:
                print("""<item not printed -- in the "don't print" list>""")
            else:
                repr_value = repr(data_element.value)
                if len(repr_value) > 50:
                    repr_value = repr_value[:50] + "..."
                print("{0:s} {1:s} = {2:s}".format(indent_string,
                                                   data_element.name,
                                                   repr_value))


def load_dcm(img_path):
    dcm = pydicom.read_file(img_path)
    RescaleIntercept = int(dcm.data_element('RescaleIntercept').value)
    img = np.array(dcm.pixel_array, dtype=np.int16) + RescaleIntercept
    return img


# 2 ^ 11 bytes = 2048
filename = "ImagensTC_Pulmao/8.dcm"
dataset = pydicom.dcmread(filename, force=True)
dataset.file_meta.TransferSyntaxUID = pydicom.uid.ImplicitVRLittleEndian
# dataset.pixel_array

# filename = get_testdata_files('MR_small.dcm')[0]
# ds = pydicom.dcmread(filename)
# myprint(ds)

# Normal mode:
print()
print("Filename.........:", filename)
print("Storage type.....:", dataset.SOPClassUID)
print()

pat_name = dataset.PatientName
display_name = pat_name.family_name + ", " + pat_name.given_name
print("Patient's name...:", display_name)
print("Patient id.......:", dataset.PatientID)
print("Modality.........:", dataset.Modality)
print("Study Date.......:", dataset.StudyDate)
# print("Bit Depth........:", dataset.pixel_array)

if 'PixelData' in dataset:
    rows = int(dataset.Rows)
    cols = int(dataset.Columns)
    print("Image size.......: {rows:d} x {cols:d}, {size:d} bytes".format(
        rows=rows, cols=cols, size=len(dataset.PixelData)))
    if 'PixelSpacing' in dataset:
        print("Pixel spacing....:", dataset.PixelSpacing)

# use .get() if not sure the item exists, and want a default value if missing
print("Slice location...:", dataset.get('SliceLocation', "(missing)"))

get_database(dataset)

# plot the image using matplotlib
plt.imshow(dataset.pixel_array, cmap=plt.bone())
plt.show()