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 load_itk(filename):
"""
This function reads a '.mhd' file using SimpleITK
and return the image array, origin and spacing of the image.
"""
# Reads the image using SimpleITK
itk_image = ReadImage(filename)
# Convert the image to a numpy array first and then
# shuffle the dimensions to get axis in the order z,y,x
ct_scan = GetArrayFromImage(itk_image)
# Read the origin of the ct_scan, will be used to convert
# the coordinates from world to voxel and vice versa.
origin = np.array(list(reversed(itk_image.GetOrigin())))
# Read the spacing along each dimension
spacing = np.array(list(reversed(itk_image.GetSpacing())))
return ct_scan, origin, spacing
def openfiles(self):
if self.file_path == "":
return
if self.name == "":
if "T2" in self.file_path.split("/")[-1]:
self.name = "T2"
if "LGE" in self.file_path.split("/")[-1]:
self.name = "LGE"
if "C0" in self.file_path.split("/")[-1]:
self.name = "C0"
if self.name == "":
self.name = "C0"
itk_img = ReadImage(self.file_path)
img = GetArrayFromImage(itk_img)
self.spacing = itk_img.GetSpacing()
self.direction = itk_img.GetDirection()
# print("img:", self.file_path, "direction:", self.direction)
self.origin = itk_img.GetOrigin()
minDim = list(img.shape).index(min(img.shape))
if minDim == 0:
self.img = np.zeros((img.shape[1], img.shape[2], min(img.shape)))
for i in range(min(img.shape)):
self.img[:, :, i] = self.showRoate(img[i, :, :])
if minDim == 1:
self.img = np.zeros((img.shape[0], img.shape[2], min(img.shape)))
for i in range(min(img.shape)):
self.img[:, :, i] = img[:, i, :]
if minDim == 2:
self.img = img
self.imgDim = self.img.shape[2]
if self.imgDim >= 3:
self.imgIndex = int(self.imgDim / 2 + 1)
else:
self.imgIndex = int(self.imgDim / 2)
self.adjusted = False
self.predicted = False
self.isOpen = True
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
def openfiles(self):
try:
imgName, imgType = QFileDialog.getOpenFileName(
self,
"",
os.getcwd(),
filter=
"nii.gz Files (*.nii.gz);;mha Files (*.mha);;nii Files (*.nii);;All Files (*)"
)
if imgName == "":
return
if "T2" in imgName:
self.name = "T2"
self.classItems.setCurrentIndex(1)
if "LGE" in imgName:
self.name = "LGE"
self.classItems.setCurrentIndex(2)
if "C0" in imgName:
self.name = "C0"
self.classItems.setCurrentIndex(0)
self.OpenPath = imgName
itk_img = ReadImage(imgName)
img = GetArrayFromImage(itk_img)
self.spacing = itk_img.GetSpacing()
self.direction = itk_img.GetDirection()
print("img:", self.openPath, "direction:", self.direction)
self.origin = itk_img.GetOrigin()
minDim = list(img.shape).index(min(img.shape))
print(minDim)
if minDim == 0:
self.img = np.zeros(
(img.shape[1], img.shape[2], min(img.shape)))
for i in range(min(img.shape)):
self.img[:, :, i] = self.adjustRoate(img[i, :, :])
if minDim == 1:
self.img = np.zeros(
(img.shape[0], img.shape[2], min(img.shape)))
for i in range(min(img.shape)):
self.img[:, :, i] = img[:, i, :]
if minDim == 2:
self.img = img
self.imgDim = self.img.shape[2]
if self.imgDim >= 3:
self.imgIndex = int(self.imgDim / 2 + 1)
else:
self.imgIndex = int(self.imgDim / 2)
plt.cla()
self.fig, self.ax = plt.subplots()
self.ax.axis('off')
self.ax.imshow(self.showRoate(self.img[:, :, self.imgIndex]),
interpolation='nearest',
aspect='auto',
cmap='gray')
cavan = FigureCanvas(self.fig)
for i in reversed(range(self.verticalLayout.count())):
self.verticalLayout.itemAt(i).widget().setParent(None)
self.verticalLayout.addWidget(cavan)
self.tableWidget.insertRow(0)
item = QTableWidgetItem(str(self.img.shape[0]))
item.setTextAlignment(Qt.AlignVCenter | Qt.AlignHCenter)
self.tableWidget.setItem(0, 0, item)
item = QTableWidgetItem(str(self.img.shape[1]))
item.setTextAlignment(Qt.AlignVCenter | Qt.AlignHCenter)
self.tableWidget.setItem(0, 1, item)
item = QTableWidgetItem(str(self.img.shape[2]))
item.setTextAlignment(Qt.AlignVCenter | Qt.AlignHCenter)
self.tableWidget.setItem(0, 2, item)
if not self.isOpen:
self.LPLabel.setText("L/P")
self.RALabel.setText("R/A")
self.ILabel.setText("I")
self.SLabel.setText("S")
self.nameLabel.setText(imgName.split("/")[-1])
self.totalCount.setText("/" + str(self.imgDim))
self.lineEdit.setText(str(self.imgIndex + 1))
self.adjusted = False
self.predicted = False
self.isOpen = True
except:
pass
