def execute(self) -> structure.BrainImage:
"""Extracts features from an image.
Returns:
structure.BrainImage: The image with extracted features.
"""
if self.coordinates_feature:
atlas_coordinates = fltr_feat.AtlasCoordinates()
self.img.feature_images[FeatureImageTypes.ATLAS_COORD] = \
atlas_coordinates.execute(self.img.images[structure.BrainImageTypes.T1])
if self.intensity_feature:
self.img.feature_images[
FeatureImageTypes.T1_INTENSITY] = self.img.images[
structure.BrainImageTypes.T1]
self.img.feature_images[
FeatureImageTypes.T2_INTENSITY] = self.img.images[
structure.BrainImageTypes.T2]
if self.gradient_intensity_feature:
# compute gradient magnitude images
self.img.feature_images[FeatureImageTypes.T1_GRADIENT_INTENSITY] = \
sitk.GradientMagnitude(self.img.images[structure.BrainImageTypes.T1])
self.img.feature_images[FeatureImageTypes.T2_GRADIENT_INTENSITY] = \
sitk.GradientMagnitude(self.img.images[structure.BrainImageTypes.T2])
self._generate_feature_matrix()
return self.img
def execute(self) -> structure.BrainImage:
"""Extracts features from an image.
Returns:
structure.BrainImage: The image with extracted features.
"""
# todo: add T2w features
warnings.warn('No features from T2-weighted image extracted.')
if self.coordinates_feature:
atlas_coordinates = fltr_feat.AtlasCoordinates()
self.img.feature_images[FeatureImageTypes.ATLAS_COORD] = \
atlas_coordinates.execute(self.img.images[structure.BrainImageTypes.T1w])
if self.intensity_feature:
self.img.feature_images[FeatureImageTypes.T1w_INTENSITY] = self.img.images[structure.BrainImageTypes.T1w]
if self.gradient_intensity_feature:
# compute gradient magnitude images
self.img.feature_images[FeatureImageTypes.T1w_GRADIENT_INTENSITY] = \
sitk.GradientMagnitude(self.img.images[structure.BrainImageTypes.T1w])
self._generate_feature_matrix()
return self.img
def execute(self) -> structure.BrainImage:
"""Extracts features from an image.
Returns:
structure.BrainImage: The image with extracted features.
"""
if self.coordinates_feature:
atlas_coordinates = fltr_feat.AtlasCoordinates()
self.img.feature_images[FeatureImageTypes.ATLAS_COORD] = \
atlas_coordinates.execute(self.img.images[structure.BrainImageTypes.T1])
if self.intensity_feature:
self.img.feature_images[FeatureImageTypes.T1_INTENSITY] = self.img.images[structure.BrainImageTypes.T1]
self.img.feature_images[FeatureImageTypes.T2_INTENSITY] = self.img.images[structure.BrainImageTypes.T2]
if self.gradient_intensity_feature:
# compute gradient magnitude images
self.img.feature_images[FeatureImageTypes.T1_GRADIENT_INTENSITY] = \
sitk.GradientMagnitude(self.img.images[structure.BrainImageTypes.T1])
self.img.feature_images[FeatureImageTypes.T2_GRADIENT_INTENSITY] = \
sitk.GradientMagnitude(self.img.images[structure.BrainImageTypes.T2])
if self.hog_feature:
hog_feat_T1 = fltr_feat.Hog_descriptor()
self.img.feature_images[FeatureImageTypes.T1_HOG] = \
hog_feat_T1.execute(self.img.images[structure.BrainImageTypes.T1])
hog_feat_T2 = fltr_feat.Hog_descriptor()
self.img.feature_images[FeatureImageTypes.T2_HOG] = \
hog_feat_T2.execute(self.img.images[structure.BrainImageTypes.T2])
if self.secondOrder_feature:
result_T1 = fltr_feat.secondOrderFeatures()
self.img.feature_images[FeatureImageTypes.T1_SECOND_ORDER] = \
result_T1.execute(self.img.images[structure.BrainImageTypes.T1])
result_T2 = fltr_feat.secondOrderFeatures()
self.img.feature_images[FeatureImageTypes.T2_SECOND_ORDER] = \
result_T2.execute(self.img.images[structure.BrainImageTypes.T2])
if self.canny_feature:
# compute gradient magnitude images
self.img.feature_images[FeatureImageTypes.T1_CANNY] = \
sitk.CannyEdgeDetection(self.img.images[structure.BrainImageTypes.T1])
self.img.feature_images[FeatureImageTypes.T2_CANNY] = \
sitk.CannyEdgeDetection(self.img.images[structure.BrainImageTypes.T2])
self._generate_feature_matrix()
return self.img
def execute(self) -> structure.BrainImage:
"""Extracts features from an image.
Returns:
structure.BrainImage: The image with extracted features.
"""
# dir 'features' is a sub-dir of a given image, containing image-features
self.feature_path = os.path.join(self.img.path, 'features')
if self.save_features:
if self.coordinates_feature:
atlas_coordinates = fltr_feat.AtlasCoordinates()
self.img.feature_images[FeatureImageTypes.ATLAS_COORD] = \
atlas_coordinates.execute(self.img.images[structure.BrainImageTypes.T1w])
if self.intensity_feature:
self.img.feature_images[
FeatureImageTypes.T1w_INTENSITY] = self.img.images[
structure.BrainImageTypes.T1w]
self.img.feature_images[
FeatureImageTypes.T2w_INTENSITY] = self.img.images[
structure.BrainImageTypes.T2w]
if self.gradient_intensity_feature:
# compute gradient magnitude images
self.img.feature_images[FeatureImageTypes.T1w_GRADIENT_INTENSITY] = \
sitk.GradientMagnitude(self.img.images[structure.BrainImageTypes.T1w])
self.img.feature_images[FeatureImageTypes.T2w_GRADIENT_INTENSITY] = \
sitk.GradientMagnitude(self.img.images[structure.BrainImageTypes.T2w])
if self.first_order_feature:
# compute first order features
fof_T1w_features = firstorder.RadiomicsFirstOrder(
self.img.images[structure.BrainImageTypes.T1w],
self.img.images[structure.BrainImageTypes.BrainMask],
voxelBased=True)
fof_T1w_features.enabledFeatures = self.first_order_feature_parameters
self.img.feature_images[
FeatureImageTypes.T1w_FOF] = fof_T1w_features.execute()
self.img.feature_images[
FeatureImageTypes.T1w_FOF] = sitk.Compose(
list(self.img.feature_images[
FeatureImageTypes.T1w_FOF].values()))
self.img.feature_images[
FeatureImageTypes.T1w_FOF].CopyInformation(
self.img.images[structure.BrainImageTypes.T1w])
fof_T2w_features = firstorder.RadiomicsFirstOrder(
self.img.images[structure.BrainImageTypes.T2w],
self.img.images[structure.BrainImageTypes.BrainMask],
voxelBased=True)
fof_T2w_features.enabledFeatures = self.first_order_feature_parameters
self.img.feature_images[
FeatureImageTypes.T2w_FOF] = fof_T2w_features.execute()
self.img.feature_images[
FeatureImageTypes.T2w_FOF] = sitk.Compose(
list(self.img.feature_images[
FeatureImageTypes.T2w_FOF].values()))
self.img.feature_images[
FeatureImageTypes.T2w_FOF].CopyInformation(
self.img.images[structure.BrainImageTypes.T2w])
if self.GLCM_features:
# compute GLCM features
glcmT1w_features = glcm.RadiomicsGLCM(
self.img.images[structure.BrainImageTypes.T1w],
self.img.images[structure.BrainImageTypes.BrainMask],
voxelBased=True)
glcmT1w_features.enabledFeatures = self.GLCM_features_parameters
self.img.feature_images[
FeatureImageTypes.T1w_GLCM] = glcmT1w_features.execute()
self.img.feature_images[
FeatureImageTypes.T1w_GLCM] = sitk.Compose(
list(self.img.feature_images[
FeatureImageTypes.T1w_GLCM].values()))
self.img.feature_images[
FeatureImageTypes.T1w_GLCM].CopyInformation(
self.img.images[structure.BrainImageTypes.T1w])
glcmT2w_features = glcm.RadiomicsGLCM(
self.img.images[structure.BrainImageTypes.T2w],
self.img.images[structure.BrainImageTypes.BrainMask],
voxelBased=True)
glcmT2w_features.enabledFeatures = self.GLCM_features_parameters
self.img.feature_images[
FeatureImageTypes.T2w_GLCM] = glcmT2w_features.execute()
self.img.feature_images[
FeatureImageTypes.T2w_GLCM] = sitk.Compose(
list(self.img.feature_images[
FeatureImageTypes.T2w_GLCM].values()))
self.img.feature_images[
FeatureImageTypes.T2w_GLCM].CopyInformation(
self.img.images[structure.BrainImageTypes.T2w])
if self.HOG_feature:
# compute 3D-HOG features with GPU support
hog_features_T1w = fltr_hog.HOGExtractorGPU(
self.img.images[structure.BrainImageTypes.T1w])
self.img.feature_images[FeatureImageTypes.T1w_HOG] = \
hog_features_T1w.execute(self.img.images[structure.BrainImageTypes.T1w])
hog_features_T2w = fltr_hog.HOGExtractorGPU(
self.img.images[structure.BrainImageTypes.T1w])
self.img.feature_images[FeatureImageTypes.T2w_HOG] = \
hog_features_T2w.execute(self.img.images[structure.BrainImageTypes.T2w])
else:
for _, name in enumerate(FeatureImageTypes):
try:
self.img.feature_images[name] = \
sitk.ReadImage(os.path.join(self.feature_path, name.name + '.nii.gz'), sitk.sitkVectorFloat32)
study_features = [
FeatureImageTypes.T1w_FOF, FeatureImageTypes.T2w_FOF,
FeatureImageTypes.T1w_HOG, FeatureImageTypes.T2w_HOG,
FeatureImageTypes.T1w_GLCM, FeatureImageTypes.T2w_GLCM
]
if name in study_features:
enabeled_features_idx = [
i for i, x in enumerate(
list(self.first_order_feature_parameters.
values())) if x == True
]
enabeled_features = [
sitk.VectorIndexSelectionCast(
self.img.feature_images[name], j)
for j in enabeled_features_idx
]
self.img.feature_images[name] = sitk.Compose(
enabeled_features, sitk.sitkVectorFloat32)
except RuntimeError:
pass
if self.save_features:
os.makedirs(self.feature_path, exist_ok=True)
for _, name in enumerate(FeatureImageTypes):
try:
sitk.WriteImage(
self.img.feature_images[name],
os.path.join(self.feature_path, name.name + '.nii.gz'))
except KeyError:
pass
self._generate_feature_matrix()
return self.img
def execute(self) -> structure.BrainImage:
"""Extracts features from an image.
Returns:
structure.BrainImage: The image with extracted features.
"""
# todo: add T2w features (Add T2w to the "self" below)
# warnings.warn('No features from T2-weighted image extracted.')
if self.coordinates_feature:
atlas_coordinates = fltr_feat.AtlasCoordinates()
self.img.feature_images[FeatureImageTypes.ATLAS_COORD] = \
atlas_coordinates.execute(self.img.images[structure.BrainImageTypes.T1w])
# Don't need for Atlas (t1 and t2 already aligned)
self.img.feature_images[FeatureImageTypes.ATLAS_COORD] = \
atlas_coordinates.execute(self.img.images[structure.BrainImageTypes.T2w])
if self.intensity_feature:
self.img.feature_images[
FeatureImageTypes.T1w_INTENSITY] = self.img.images[
structure.BrainImageTypes.T1w]
self.img.feature_images[
FeatureImageTypes.T2w_INTENSITY] = self.img.images[
structure.BrainImageTypes.T2w]
if self.gradient_intensity_feature:
# compute gradient magnitude images
self.img.feature_images[FeatureImageTypes.T1w_GRADIENT_INTENSITY] = \
sitk.GradientMagnitude(self.img.images[structure.BrainImageTypes.T1w])
self.img.feature_images[FeatureImageTypes.T2w_GRADIENT_INTENSITY] = \
sitk.GradientMagnitude(self.img.images[structure.BrainImageTypes.T2w])
#Atlas features
if self.atlas_feature_grey_matter:
self.img.feature_images[
FeatureImageTypes.Atlas_Grey_matter] = sitk.ReadImage(
'C:/Users/Admin/PycharmProjects/MyMIALab/bin/custom_atlas_result/grey_matter_map_no_threshold.nii'
)
if self.atlas_feature_white_matter:
self.img.feature_images[
FeatureImageTypes.Atlas_White_matter] = sitk.ReadImage(
'C:/Users/Admin/PycharmProjects/MyMIALab/bin/custom_atlas_result/white_matter_map_no_threshold.nii'
)
if self.atlas_feature_thalamus:
self.img.feature_images[
FeatureImageTypes.Atlas_Thalamus] = sitk.ReadImage(
'C:/Users/Admin/PycharmProjects/MyMIALab/bin/custom_atlas_result/thalamus_map_no_threshold.nii'
)
if self.atlas_feature_amygdala:
self.img.feature_images[
FeatureImageTypes.Atlas_Amygdala] = sitk.ReadImage(
'C:/Users/Admin/PycharmProjects/MyMIALab/bin/custom_atlas_result/amygdala_map_no_threshold.nii'
)
if self.atlas_feature_hippocampus:
self.img.feature_images[
FeatureImageTypes.Atlas_Hippocampus] = sitk.ReadImage(
'C:/Users/Admin/PycharmProjects/MyMIALab/bin/custom_atlas_result/hippocampus_map_no_threshold.nii'
)
self._generate_feature_matrix()
return self.img
