def extractPatch_2D_patchs_landmark(self):
""" This function extraccts 2D patches using land marks from an XML file"""
if self.appply_on_batch_files is False: # single image
img_name = self.image_name
img_name = os.path.split(img_name)
img_name = img_name[-1]
img_name_split = img_name.split(".")
self.img_name_ = img_name_split[0]
# convert image to 8 bit
self.data = self.to_8bit_(self.data)
self.do_2D_patch_extraction()
else:
assert len(os.listdir(self.img_source_folder)) or \
len(os.listdir(self.xml_source_folder)), 'source folder is empty'
assert len(os.listdir(self.xml_source_folder)) == len(os.listdir(self.img_source_folder)), \
'number of xml file and image files shoud be same, BUT, found different'
img_files = os.listdir(self.img_source_folder)
xml_files = os.listdir(self.xml_source_folder)
for images_name, xml_name in zip(img_files, xml_files):
self.image_name = images_name
# get image extension
img_name = self.image_name
img_name = os.path.split(img_name)
img_name = img_name[-1]
img_name_split = img_name.split(".")
self.img_name_ = img_name_split[0]
img_extension = img_name_split[-1]
name_ = os.path.join(self.img_source_folder, images_name)
if img_extension == 'dcm':
self.data = read_dicom(name_)
elif img_extension == 'nii' or img_extension == 'gz' or img_extension == 'nii.gz':
self.data = read_nii(name_)
else:
self.data = read_image(name_)
# convert image to 8 bit
self.data = self.to_8bit_(self.data)
# read XML file
self.landmark_path = os.path.join(self.xml_source_folder,
xml_name)
lmark = get_type_center_from_XML(self.landmark_path)
self.landmark = lmark
# apply augmentation
self.do_2D_patch_extraction()
print('Patch Generation done!')
def load_reference_image(self):
filter = "All Files (*);;image files (*.nii.gz *.png *.tif *.PNG *.dcm)"
title = "Select refernce image"
ref_image_name = self.openFileNameDialog(filter, title)
# self.ref_image = io.imread(image_name)
# get image extension
img_name = ref_image_name
img_name = os.path.split(img_name)
img_name = img_name[-1]
img_name_split = img_name.split(".")
img_extension = img_name_split[-1]
if img_extension == 'dcm':
self.ref_image = read_dicom(ref_image_name)
elif img_extension == 'nii' or img_extension == 'gz' or img_extension == 'nii.gz':
self.ref_image = read_nii(ref_image_name)
else:
self.ref_image = read_image(ref_image_name)
def apply_otherpreprocessing(self):
"""
this function cheks if it the operation is requested on a single image or to abatch files and call
the respective function
:return:
"""
if self.appply_on_batch_files is False: # single image
img_name = self.image_name
img_name = os.path.split(img_name)
img_name = img_name[-1]
img_name_split = img_name.split(".")
self.img_name_ = img_name_split[0]
self.do_preprocessing()
else: # apply to all images in the folder
assert len(os.listdir()), 'source folder is empty'
files = os.listdir(self.source_folder)
for images_name in files:
self.image_name = images_name
# get image extension
img_name = self.image_name
img_name = os.path.split(img_name)
img_name = img_name[-1]
img_name_split = img_name.split(".")
self.img_name_ = img_name_split[0]
img_extension = img_name_split[-1]
name_ = os.path.join(self.source_folder, images_name)
if img_extension == 'dcm':
self.input_image = read_dicom(name_)
elif img_extension == 'nii' or img_extension == 'gz' or img_extension == 'nii.gz':
self.input_image = read_nii(name_)
else:
self.input_image = read_image(name_)
self.do_preprocessing()
print('All requested preprcessing are done!')
def loadImageimage_data(self, apply_to_folder_files=False):
if apply_to_folder_files is True:
self.source_folder = str(
QFileDialog.getExistingDirectory(
self, "Select a directory containing images"))
if os.path.isdir(self.source_folder) is False or len(
os.listdir(self.source_folder)) is 0:
QMessageBox.warning(
self, "Warning",
"Please select a folder or the directory is empty")
else:
self.image_data = None
self.image_name = None
else:
filter = "All Files (*);;image files (*.nii.gz *.png *.tif *.PNG *.dcm)"
title = "Select image or folder"
self.image_name = self.openFileNameDialog(filter, title)
if os.path.isdir(self.image_name) is True:
print('you have selected a folder, please select a file!')
else:
# get image extension
img_name = self.image_name
img_name = os.path.split(img_name)
img_name = img_name[-1]
img_name_split = img_name.split(".")
img_extension = img_name_split[-1]
# allowed image formats
image_format = ('.png', '.PNG', '.tif', '.dcm', '.nii',
'nii.gz')
assert self.image_name.endswith(image_format) is True, 'selected file doesnot have supported image extension. allowed image ' \
'image extensions are (.png, .PNG, .tif, .dcm, .nii, nii.gz)'
if img_extension == 'dcm':
self.image_data = read_dicom(self.image_name)
elif img_extension == 'nii' or img_extension == 'gz' or img_extension == 'nii.gz':
self.image_data = read_nii(self.image_name)
else:
self.image_data = read_image(self.image_name)
# display image
# imaage shape
S = self.image_data.shape
if len(S) == 2: # 2d image
self.slider.setMinimum(0)
self.slider.setMaximum(0)
self.displayNDArray(self.image_data)
else: # 3D image
N = S[-1]
self.slider.setMinimum(0)
self.slider.setMaximum(N - 1)
self.slider.setValue(int(N / 2))
self.slider.setTickInterval(1)
self.displayNDArray(self.image_data[:, :, int(N / 2)])
def extractPatch_2D5_patchs_mask_gt(self):
"""
Extract 2.5D patches from 3D image with ground truth image provided.
"""
# the size of the patch will only depend on the first patchg dimension
patch_size_temp = (self.patch_dim[0], self.patch_dim[0],
self.patch_dim[0])
if self.appply_on_batch_files is False: # single image
# get image name and extension
img_name = self.image_name
img_name = os.path.split(img_name)
img_name = img_name[-1]
img_name_split = img_name.split(".")
self.img_name_ = img_name_split[0]
# for gt image
gt_image_name = self.gt_img_path
# get image extension
gt_image_name = os.path.split(gt_image_name)
gt_image_name = gt_image_name[-1]
gt_img_name_split = gt_image_name.split(".")
gt_img_extension = gt_img_name_split[-1]
name_ = os.path.join(self.gt_img_path)
if gt_img_extension == 'dcm':
self.gt_data = read_dicom(name_)
elif gt_img_extension == 'nii' or gt_img_extension == 'gz' or gt_img_extension == 'nii.gz':
self.gt_data = read_nii(name_)
else:
self.gt_data = read_image(name_)
# convert to 8 bit
self.data = self.to_8bit_(self.data)
# extract and save patchs
im_patches, gt_patches = extract_3d_patches(self.data,
patch_size_temp,
self.stride,
gt_data=self.gt_data)
output_patches = self.make_2D5_patch_from_3d(im_patches)
path_ = os.path.join(self.generated_patches_folder,
self.img_name_ + '_images_.npy')
np.save(path_, output_patches)
output_patches_gt = self.make_2D5_patch_from_3d(gt_patches)
path_ = os.path.join(self.generated_patches_folder,
self.img_name_ + '_gt_.npy')
np.save(path_, output_patches_gt)
else: # for batch of files
assert len(os.listdir(self.img_source_folder)) or \
len(os.listdir(self.gt_path_source_folder)), 'source folder is empty'
assert len(os.listdir(self.gt_path_source_folder)) == len(os.listdir(self.img_source_folder)), \
'number of xml file and image files shoud be same, BUT, found different'
img_files = os.listdir(self.img_source_folder)
gt_files = os.listdir(self.gt_path_source_folder)
for images_name, gt_name in zip(img_files, gt_files):
self.image_name = images_name
# get image extension
img_name = self.image_name
img_name = os.path.split(img_name)
img_name = img_name[-1]
img_name_split = img_name.split(".")
self.img_name_ = img_name_split[0]
img_extension = img_name_split[-1]
name_ = os.path.join(self.img_source_folder, images_name)
if img_extension == 'dcm':
self.data = read_dicom(name_)
elif img_extension == 'nii' or img_extension == 'gz' or img_extension == 'nii.gz':
self.data = read_nii(name_)
else:
self.data = read_image(name_)
# convert to 8-bit
self.data = self.to_8bit_(self.data)
# for gt image
gt_image_name = gt_name
# get image extension
gt_image_name = os.path.split(gt_image_name)
gt_image_name = gt_image_name[-1]
gt_img_name_split = gt_image_name.split(".")
gt_image_name = gt_img_name_split[0]
gt_img_extension = gt_img_name_split[-1]
name_ = os.path.join(self.gt_path_source_folder, gt_name)
if gt_img_extension == 'dcm':
self.gt_data = read_dicom(name_)
elif gt_img_extension == 'nii' or img_extension == 'gz' or img_extension == 'nii.gz':
self.gt_data = read_nii(name_)
else:
self.gt_data = read_image(name_)
# extract and save patchs
im_patches, gt_patches = extract_3d_patches(
self.data,
patch_size_temp,
self.stride,
gt_data=self.gt_data)
output_patches = self.make_2D5_patch_from_3d(im_patches)
path_ = os.path.join(self.generated_patches_folder,
self.img_name_ + '_images_.npy')
np.save(path_, output_patches)
output_patches_gt = self.make_2D5_patch_from_3d(gt_patches)
path_ = os.path.join(self.generated_patches_folder,
self.img_name_ + '_gt_.npy')
np.save(path_, output_patches_gt)
print('Patch Generation done!')
def extractPatch_2D5_patchs_no_gt(self):
"""
Extract 2.5D patches from 3D image; when there is no ground truth provided.
"""
patch_size_temp = (self.patch_dim[0], self.patch_dim[0],
self.patch_dim[0])
if self.appply_on_batch_files is False: # single image
img_name = self.image_name
img_name = os.path.split(img_name)
img_name = img_name[-1]
img_name_split = img_name.split(".")
self.img_name_ = img_name_split[0]
self.data = self.to_8bit_(self.data)
im_patches = extract_3d_patches(self.data,
patch_size_temp,
self.stride,
gt_data=None)
output_patches = self.make_2D5_patch_from_3d(im_patches)
path_ = os.path.join(self.generated_patches_folder,
self.img_name_ + '_images_.npy')
np.save(path_, output_patches)
else: # for batch of files
assert len(os.listdir(
self.img_source_folder)), 'source folder is empty'
img_files = os.listdir(self.img_source_folder)
for images_name in img_files:
self.image_name = images_name
# get image extension
img_name = self.image_name
img_name = os.path.split(img_name)
img_name = img_name[-1]
img_name_split = img_name.split(".")
self.img_name_ = img_name_split[0]
img_extension = img_name_split[-1]
name_ = os.path.join(self.img_source_folder, images_name)
if img_extension == 'dcm':
self.data = read_dicom(name_)
elif img_extension == 'nii' or img_extension == 'gz' or img_extension == 'nii.gz':
self.data = read_nii(name_)
else:
self.data = read_image(name_)
# convert to 8-bit
self.data = self.to_8bit_(self.data)
# extract and save patchs
im_patches = extract_3d_patches(self.data,
patch_size_temp,
self.stride,
gt_data=None)
output_patches = self.make_2D5_patch_from_3d(im_patches)
path_ = os.path.join(self.generated_patches_folder,
self.img_name_ + '_images_.npy')
np.save(path_, output_patches)
print('Patch Generation done!')
def extractPatch_3D_patchs_mask_gt(self):
"""
This function it extarcts 3D patches using mask or ground truth or ROI image into consideration
"""
if self.appply_on_batch_files is False: # single image
# get image name and extension
img_name = self.image_name
img_name = os.path.split(img_name)
img_name = img_name[-1]
img_name_split = img_name.split(".")
self.img_name_ = img_name_split[0]
# for gt image
gt_image_name = self.gt_img_path
# get image extension
gt_image_name = os.path.split(gt_image_name)
gt_image_name = gt_image_name[-1]
gt_img_name_split = gt_image_name.split(".")
gt_img_extension = gt_img_name_split[-1]
name_ = os.path.join(self.gt_img_path)
if gt_img_extension == 'dcm':
self.gt_data = read_dicom(name_)
elif gt_img_extension == 'nii' or gt_img_extension == 'gz' or gt_img_extension == 'nii.gz':
self.gt_data = read_nii(name_)
else:
self.gt_data = read_image(name_)
# convert to 8-bit
self.data = self.to_8bit_(self.data)
# extract patch
im_patches, gt_patches = extract_3d_patches(self.data,
self.patch_dim,
self.stride,
gt_data=self.gt_data)
# save patch
path_ = os.path.join(self.generated_patches_folder,
self.img_name_ + '_images_.npy')
np.save(path_, im_patches)
path_ = os.path.join(self.generated_patches_folder,
self.img_name_ + '_gt_.npy')
np.save(path_, gt_patches)
else: # for batch of files
assert len(os.listdir(self.img_source_folder)) or \
len(os.listdir(self.gt_path_source_folder)), 'source folder is empty'
assert len(os.listdir(self.gt_path_source_folder)) == len(os.listdir(self.img_source_folder)), \
'number of xml file and image files shoud be same, BUT, found different'
img_files = os.listdir(self.img_source_folder)
gt_files = os.listdir(self.gt_path_source_folder)
for images_name, gt_name in zip(img_files, gt_files):
self.image_name = images_name
# get image extension
img_name = self.image_name
img_name = os.path.split(img_name)
img_name = img_name[-1]
img_name_split = img_name.split(".")
self.img_name_ = img_name_split[0]
img_extension = img_name_split[-1]
name_ = os.path.join(self.img_source_folder, images_name)
if img_extension == 'dcm':
self.data = read_dicom(name_)
elif img_extension == 'nii' or img_extension == 'gz' or img_extension == 'nii.gz':
self.data = read_nii(name_)
else:
self.data = read_image(name_)
# convert to 8-bit
self.data = self.to_8bit_(self.data)
# for gt image
gt_image_name = gt_name
# get image extension
gt_image_name = os.path.split(gt_image_name)
gt_image_name = gt_image_name[-1]
gt_img_name_split = gt_image_name.split(".")
gt_image_name = gt_img_name_split[0]
gt_img_extension = gt_img_name_split[-1]
name_ = os.path.join(self.gt_path_source_folder, gt_name)
if gt_img_extension == 'dcm':
self.gt_data = read_dicom(name_)
elif gt_img_extension == 'nii' or img_extension == 'gz' or img_extension == 'nii.gz':
self.gt_data = read_nii(name_)
else:
self.gt_data = read_image(name_)
# extract 3D patches
im_patches, gt_patches = extract_3d_patches(
self.data,
self.patch_dim,
self.stride,
gt_data=self.gt_data)
# Save patches
path_ = os.path.join(self.generated_patches_folder,
self.img_name_ + '_images_.npy')
np.save(path_, im_patches)
path_ = os.path.join(self.generated_patches_folder,
self.img_name_ + '_gt_.npy')
np.save(path_, gt_patches)
print('Patch Generation done!')
def extractPatch_2D_patchs_mask_gt(self):
if self.appply_on_batch_files is False: # single image
# get image extension
img_name = self.image_name
img_name = os.path.split(img_name)
img_name = img_name[-1]
img_name_split = img_name.split(".")
self.img_name_ = img_name_split[0]
# for gt image
gt_image_name = self.gt_img_path
# get image extension
gt_image_name = os.path.split(gt_image_name)
gt_image_name = gt_image_name[-1]
gt_img_name_split = gt_image_name.split(".")
# gt_image_name = img_name_split[0]
gt_img_extension = gt_img_name_split[-1]
# Read an image
name_ = os.path.join(self.gt_img_path)
if gt_img_extension == 'dcm':
self.gt_data = read_dicom(name_)
elif gt_img_extension == 'nii' or gt_img_extension == 'gz' or gt_img_extension == 'nii.gz':
self.gt_data = read_nii(name_)
else:
self.gt_data = read_image(name_)
Dim = self.data.shape
if len(Dim) is 2: # 2D image
# extract patches
im_patches, gt_patches = extract_2d_patches(
self.data,
self.patch_dim[:2],
self.stride,
gt_data=self.gt_data)
path_ = os.path.join(self.generated_patches_folder,
self.img_name_ + '_images_.npy')
np.save(path_, im_patches)
path_ = os.path.join(self.generated_patches_folder,
self.img_name_ + '_gt_.npy')
np.save(path_, gt_patches)
else: # image is 3D and apply per slice
P_im = np.empty(
shape=[0, self.patch_dim[0], self.patch_dim[1]],
dtype='int16')
P_gt = np.empty(
shape=[0, self.patch_dim[0], self.patch_dim[1]],
dtype='int16')
for i in range(Dim[2]):
# extract slices per slice
im_patches, gt_patches = extract_2d_patches(
self.data[:, :, i],
self.patch_dim[:2],
self.stride,
gt_data=self.gt_data[:, :, i])
P_im = np.append(P_im, im_patches, axis=0)
P_gt = np.append(P_gt, gt_patches, axis=0)
path_ = os.path.join(self.generated_patches_folder,
self.img_name_ + '_images_.npy')
np.save(path_, P_im)
path_ = os.path.join(self.generated_patches_folder,
self.img_name_ + '_gt_.npy')
np.save(path_, P_gt)
else: # for batch of files
assert len(os.listdir(self.img_source_folder)) or \
len(os.listdir(self.gt_path_source_folder)), 'source folder is empty'
assert len(os.listdir(self.gt_path_source_folder)) == len(os.listdir(self.img_source_folder)), \
'number of ground truth file and image files shoud be same, BUT, found different!'
img_files = os.listdir(self.img_source_folder)
gt_files = os.listdir(self.gt_path_source_folder)
for images_name, gt_name in zip(img_files, gt_files):
self.image_name = images_name
# get image extension
img_name = self.image_name
img_name = os.path.split(img_name)
img_name = img_name[-1]
img_name_split = img_name.split(".")
self.img_name_ = img_name_split[0]
img_extension = img_name_split[-1]
name_ = os.path.join(self.img_source_folder, images_name)
if img_extension == 'dcm':
self.data = read_dicom(name_)
elif img_extension == 'nii' or img_extension == 'gz' or img_extension == 'nii.gz':
self.data = read_nii(name_)
else:
self.data = read_image(name_)
# Convert to 8 bit
self.data = self.to_8bit_(self.data)
# for gt image
gt_image_name = gt_name
# get image extension
gt_image_name = os.path.split(gt_image_name)
gt_image_name = gt_image_name[-1]
gt_img_name_split = gt_image_name.split(".")
gt_image_name = gt_img_name_split[0]
gt_img_extension = gt_img_name_split[-1]
name_ = os.path.join(self.gt_path_source_folder, gt_name)
if gt_img_extension == 'dcm':
self.gt_data = read_dicom(name_)
elif gt_img_extension == 'nii' or img_extension == 'gz' or img_extension == 'nii.gz':
self.gt_data = read_nii(name_)
else:
self.gt_data = read_image(name_)
Dim = self.data.shape
# 2D image
if len(Dim) is 2:
im_patches, gt_patches = extract_2d_patches(
self.data,
self.patch_dim[:2],
self.stride,
gt_data=self.gt_data)
path_ = os.path.join(self.generated_patches_folder,
self.img_name_ + '_images_.npy')
np.save(path_, im_patches)
path_ = os.path.join(self.generated_patches_folder,
self.img_name_ + '_gt_.npy')
np.save(path_, gt_patches)
else: # image is 3D and apply per slice
P_im = np.empty(
shape=[0, self.patch_dim[0], self.patch_dim[1]],
dtype='int16')
P_gt = np.empty(
shape=[0, self.patch_dim[0], self.patch_dim[1]],
dtype='int16')
for i in range(Dim[2]):
# extract slices per slice
im_patches, gt_patches = extract_2d_patches(
self.data[:, :, i],
self.patch_dim[:2],
self.stride,
gt_data=self.gt_data[:, :, i])
P_im = np.append(P_im, im_patches, axis=0)
P_gt = np.append(P_gt, gt_patches, axis=0)
path_ = os.path.join(self.generated_patches_folder,
self.img_name_ + '_images_.npy')
np.save(path_, P_im)
path_ = os.path.join(self.generated_patches_folder,
self.img_name_ + '_gt_.npy')
np.save(path_, P_gt)
print('Patch Generation done!')
def extractPatch_2D_patchs_no_gt(self):
if self.appply_on_batch_files is False: # single image
# get image name and extension
img_name = self.image_name
img_name = os.path.split(img_name)
img_name = img_name[-1]
img_name_split = img_name.split(".")
self.img_name_ = img_name_split[0]
# check dimenation of the data
Dim = self.data.shape
self.data = self.to_8bit_(self.data)
# 2D image
if len(Dim) is 2:
# extract patches
im_patches = extract_2d_patches(self.data,
self.patch_dim[:2],
self.stride,
gt_data=None)
# patch name
path_ = os.path.join(self.generated_patches_folder,
self.img_name_ + '_images_.npy')
#save as npy file
np.save(path_, im_patches)
else: # image is 3D and apply per slice
P = np.empty(shape=[0, self.patch_dim[0], self.patch_dim[1]],
dtype='int16')
for i in range(Dim[2]):
# extract slices per slice
data_ = self.to_8bit_(self.data[:, :, i])
im_patches = extract_2d_patches(data_,
self.patch_dim[:2],
self.stride,
gt_data=None)
P = np.append(P, im_patches, axis=0)
path_ = os.path.join(self.generated_patches_folder,
self.img_name_ + '_images_.npy')
np.save(path_, P)
else: # for batch of files
# check if folder contains file
assert len(os.listdir(
self.img_source_folder)), 'source folder is empty'
# read all files
img_files = os.listdir(self.img_source_folder)
for images_name in img_files:
self.image_name = images_name
# get image extension
img_name = self.image_name
img_name = os.path.split(img_name)
img_name = img_name[-1]
img_name_split = img_name.split(".")
self.img_name_ = img_name_split[0]
img_extension = img_name_split[-1]
name_ = os.path.join(self.img_source_folder, images_name)
if img_extension == 'dcm':
self.data = read_dicom(name_)
elif img_extension == 'nii' or img_extension == 'gz' or img_extension == 'nii.gz':
self.data = read_nii(name_)
else:
self.data = read_image(name_)
# check dimenation of the data
Dim = self.data.shape
# 2D image
if len(Dim) is 2:
im_patches = extract_2d_patches(self.data,
self.patch_dim[:2],
self.stride,
gt_data=None)
path_ = os.path.join(self.generated_patches_folder,
self.img_name_ + '_images_.npy')
np.save(path_, im_patches)
else: # image is 3D and apply per slice
P = np.empty(
shape=[0, self.patch_dim[0], self.patch_dim[1]],
dtype='int16')
for i in range(Dim[2]):
# extract slices per slice
im_patches = extract_2d_patches(self.data[:, :, i],
self.patch_dim[:2],
self.stride,
gt_data=None)
P = np.append(P, im_patches, axis=0)
path_ = os.path.join(self.generated_patches_folder,
self.img_name_ + '_images_.npy')
np.save(path_, P)