1 Introduction
In order to be able to edit Dicom images on Labelme, the reading of Dicom files in the python environment is studied here. In the Dicom image, the window width and window level of CT is a very important concept, but after looking for a long time, there is no relevant setting function in pydicom, which is different from DCMTK. But the CT value of the CT image can be obtained according to two tags, that is (0028|1052): rescale intercept and (0028|1053): rescale slope. Then the CT image is obtained according to the following operator, and then the window width and window level can be adjusted.
Hu = pixel * slope + interceptAs for the window width and window position of that part, you can Baidu by yourself.
2. Code implementation
# -*- coding=utf-8 -*-
import matplotlib.pyplot as plt
import pydicom
import pydicom.uid
import sys
import PIL.Image as Image
from PyQt5 import QtGui
import osStep1: Read Dicom image data and get CT value image (CT map)
have_numpy = True
try:
import numpy
except ImportError:
have_numpy = False
raise
sys_is_little_endian = (sys.byteorder == 'little')
NumpySupportedTransferSyntaxes = [
pydicom.uid.ExplicitVRLittleEndian,
pydicom.uid.ImplicitVRLittleEndian,
pydicom.uid.DeflatedExplicitVRLittleEndian,
pydicom.uid.ExplicitVRBigEndian,
]
# 支持的传输语法
def supports_transfer_syntax(dicom_dataset):
"""
Returns
-------
bool
True if this pixel data handler might support this transfer syntax.
False to prevent any attempt to try to use this handler
to decode the given transfer syntax
"""
return (dicom_dataset.file_meta.TransferSyntaxUID in
NumpySupportedTransferSyntaxes)
def needs_to_convert_to_RGB(dicom_dataset):
return False
def should_change_PhotometricInterpretation_to_RGB(dicom_dataset):
return False
# 加载Dicom图像数据
def get_pixeldata(dicom_dataset):
"""If NumPy is available, return an ndarray of the Pixel Data.
Raises
------
TypeError
If there is no Pixel Data or not a supported data type.
ImportError
If NumPy isn't found
NotImplementedError
if the transfer syntax is not supported
AttributeError
if the decoded amount of data does not match the expected amount
Returns
-------
numpy.ndarray
The contents of the Pixel Data element (7FE0,0010) as an ndarray.
"""
if (dicom_dataset.file_meta.TransferSyntaxUID not in
NumpySupportedTransferSyntaxes):
raise NotImplementedError("Pixel Data is compressed in a "
"format pydicom does not yet handle. "
"Cannot return array. Pydicom might "
"be able to convert the pixel data "
"using GDCM if it is installed.")
# 设置窗宽窗位
#dicom_dataset.
if not have_numpy:
msg = ("The Numpy package is required to use pixel_array, and "
"numpy could not be imported.")
raise ImportError(msg)
if 'PixelData' not in dicom_dataset:
raise TypeError("No pixel data found in this dataset.")
# Make NumPy format code, e.g. "uint16", "int32" etc
# from two pieces of info:
# dicom_dataset.PixelRepresentation -- 0 for unsigned, 1 for signed;
# dicom_dataset.BitsAllocated -- 8, 16, or 32
if dicom_dataset.BitsAllocated == 1:
# single bits are used for representation of binary data
format_str = 'uint8'
elif dicom_dataset.PixelRepresentation == 0:
format_str = 'uint{}'.format(dicom_dataset.BitsAllocated)
elif dicom_dataset.PixelRepresentation == 1:
format_str = 'int{}'.format(dicom_dataset.BitsAllocated)
else:
format_str = 'bad_pixel_representation'
try:
numpy_dtype = numpy.dtype(format_str)
except TypeError:
msg = ("Data type not understood by NumPy: "
"format='{}', PixelRepresentation={}, "
"BitsAllocated={}".format(
format_str,
dicom_dataset.PixelRepresentation,
dicom_dataset.BitsAllocated))
raise TypeError(msg)
if dicom_dataset.is_little_endian != sys_is_little_endian:
numpy_dtype = numpy_dtype.newbyteorder('S')
pixel_bytearray = dicom_dataset.PixelData
if dicom_dataset.BitsAllocated == 1:
# if single bits are used for binary representation, a uint8 array
# has to be converted to a binary-valued array (that is 8 times bigger)
try:
pixel_array = numpy.unpackbits(
numpy.frombuffer(pixel_bytearray, dtype='uint8'))
except NotImplementedError:
# PyPy2 does not implement numpy.unpackbits
raise NotImplementedError(
'Cannot handle BitsAllocated == 1 on this platform')
else:
pixel_array = numpy.frombuffer(pixel_bytearray, dtype=numpy_dtype)
length_of_pixel_array = pixel_array.nbytes
expected_length = dicom_dataset.Rows * dicom_dataset.Columns
if ('NumberOfFrames' in dicom_dataset and
dicom_dataset.NumberOfFrames > 1):
expected_length *= dicom_dataset.NumberOfFrames
if ('SamplesPerPixel' in dicom_dataset and
dicom_dataset.SamplesPerPixel > 1):
expected_length *= dicom_dataset.SamplesPerPixel
if dicom_dataset.BitsAllocated > 8:
expected_length *= (dicom_dataset.BitsAllocated // 8)
padded_length = expected_length
if expected_length & 1:
padded_length += 1
if length_of_pixel_array != padded_length:
raise AttributeError(
"Amount of pixel data %d does not "
"match the expected data %d" %
(length_of_pixel_array, padded_length))
if expected_length != padded_length:
pixel_array = pixel_array[:expected_length]
if should_change_PhotometricInterpretation_to_RGB(dicom_dataset):
dicom_dataset.PhotometricInterpretation = "RGB"
if dicom_dataset.Modality.lower().find('ct') >= 0: # CT图像需要得到其CT值图像
pixel_array = pixel_array * dicom_dataset.RescaleSlope + dicom_dataset.RescaleIntercept # 获得图像的CT值
pixel_array = pixel_array.reshape(dicom_dataset.Rows, dicom_dataset.Columns*dicom_dataset.SamplesPerPixel)
return pixel_array, dicom_dataset.Rows, dicom_dataset.Columnsstep2: Set the window width and window level for CT images
# 调整CT图像的窗宽窗位
def setDicomWinWidthWinCenter(img_data, winwidth, wincenter, rows, cols):
img_temp = img_data
img_temp.flags.writeable = True
min = (2 * wincenter - winwidth) / 2.0 + 0.5
max = (2 * wincenter + winwidth) / 2.0 + 0.5
dFactor = 255.0 / (max - min)
for i in numpy.arange(rows):
for j in numpy.arange(cols):
img_temp[i, j] = int((img_temp[i, j]-min)*dFactor)
min_index = img_temp < 0
img_temp[min_index] = 0
max_index = img_temp > 255
img_temp[max_index] = 255
return img_tempstep3: Get the tag information in Dicom
The first way:
# 加载Dicom图片中的Tag信息
def loadFileInformation(filename):
information = {}
ds = pydicom.read_file(filename)
information['PatientID'] = ds.PatientID
information['PatientName'] = ds.PatientName
information['PatientBirthDate'] = ds.PatientBirthDate
information['PatientSex'] = ds.PatientSex
information['StudyID'] = ds.StudyID
information['StudyDate'] = ds.StudyDate
information['StudyTime'] = ds.StudyTime
information['InstitutionName'] = ds.InstitutionName
information['Manufacturer'] = ds.Manufacturer
print(dir(ds))
print(type(information))
return informationthe second way
dcm = pydicom.dcmread(fileanme) # 加载Dicom数据
print(dcm[0x0008, 0x0060])
>>(0008, 0060) Modality CS: 'MR'
print(dcm[0x0008, 0x0060].VR)
>>CS
print(dcm[0x0008, 0x0060].value)
>>MRstep4: Convert Dicom image data to PIL.Image
dcm = pydicom.dcmread(fileanme) # 加载Dicom数据
dcm_img = Image.fromarray(img_data) # 将Numpy转换为PIL.Image
dcm_img = dcm_img.convert('L')
# 保存为jpg文件，用作后面的生成label用
dcm_img.save('temp.jpg')
# 显示图像
dcm_img.show()3. Results display
Brain CT image with window width and window level adjusted:
