def readdcmfile(filename):
"""
This function used to read information from dicom file.
Input:
filename: file path to dicom file.
Returns:
spacing, machine, image_array, shape
Note.: SimpleITK read image in the order of z-y-x, namely the number of slice-width-height;
However,SimpleITK read origin and spacing in the order of x-y-z.
"""
image = ReadImage(filename)
machine = image.GetMetaData('0008|0070')
manufacturer_model_name = image.GetMetaData('0008|1090')
image_array = GetArrayFromImage(image) # in the order of z, y, x
shape = image.GetSize()
# origin = image.GetOrigin() # in the order of x, y, z
spacing = image.GetSpacing() # in the order of x, y, z
return spacing, machine, manufacturer_model_name, image_array, shape
def resample(sel, old_image_path, datatype='series'):
"""
Usage: resample(sel, old_image_path)
Resample a 3D old_image to given new spacing
The new voxel spacing will determine the new old_image dimensions.
interpolation选项 所用的插值方法
INTER_NEAREST 最近邻插值
INTER_LINEAR 双线性插值（默认设置）
INTER_AREA 使用像素区域关系进行重采样。 它可能是图像抽取的首选方法，因为它会产生无云纹理的结果。 但是当图像缩放时，它类似于INTER_NEAREST方法。
INTER_CUBIC 4x4像素邻域的双三次插值
INTER_LANCZOS4 8x8像素邻域的Lanczos插值
"""
# read dicom series
if datatype == 'series':
reader = ImageSeriesReader()
dicom_names = reader.GetGDCMSeriesFileNames(old_image_path)
reader.SetFileNames(dicom_names)
reader.MetaDataDictionaryArrayUpdateOn()
reader.LoadPrivateTagsOn()
series_ids = reader.GetGDCMSeriesIDs(
old_image_path) # get all series id
series_file_names = reader.GetGDCMSeriesFileNames(
old_image_path, series_ids[0]) # get the first series
reader.SetFileNames(series_file_names)
old_image = reader.Execute() # type: sitk.Image
elif datatype == 'nii':
# read nifiti file
old_image = ReadImage(old_image_path)
else:
print(f'Datatype {datatype} is wrong!\n')
# get old information and new information
old_spacing = old_image.GetSpacing()
size = old_image.GetSize()
new_size = (np.round(
size * (old_spacing / sel._new_spacing))).astype(int).tolist()
# EXE
# If is orginal data ('series'), use sitk.sitkLinear.
# If is binary mask ('nii'), usse sitk.sitkNearestNeighbor.
# TODO: other methods;
# FIXME: Some cases the 'series' may not indicate the orginal data
# FIXME:Some cases the 'nii' may not indicate the binary mask
if datatype == 'series':
resampled_img = sitk.Resample(old_image, new_size,
sitk.Transform(), sitk.sitkLinear,
old_image.GetOrigin(),
sel._new_spacing,
old_image.GetDirection(), 0.0,
old_image.GetPixelID())
elif datatype == 'nii':
resampled_img = sitk.Resample(old_image, new_size,
sitk.Transform(),
sitk.sitkNearestNeighbor,
old_image.GetOrigin(),
sel._new_spacing,
old_image.GetDirection(), 0.0,
old_image.GetPixelID())
# resampled_img.GetSpacing()
# resampled_img.GetSize()
return resampled_img