plt.subplot(132)
plt.imshow(phantom_tm[:,128,:],vmin=0, vmax=1)
plt.title('3D Phantom, coronal view')
plt.subplot(133)
plt.imshow(phantom_tm[:,:,128],vmin=0, vmax=1)
plt.title('3D Phantom, sagittal view')
plt.show()
print ("Building a subset of 3D projection data using TomoPhantom software")
Horiz_det = int(np.sqrt(2)*N_size) # detector column count (horizontal)
Vert_det = N_size # detector row count (vertical) (no reason for it to be > N)
angles_num = int(0.5*np.pi*N_size); # angles number
angles = np.linspace(0.0,179.9,angles_num,dtype='float32') # in degrees
projData3D_cut = TomoP3D.ModelSinoSub(model, N_size, Horiz_det, Vert_det, DIM_z, angles, path_library3D)
intens_max = 60
plt.figure()
plt.subplot(131)
plt.imshow(projData3D_cut[:,sliceSel,:],vmin=0, vmax=intens_max)
plt.title('2D Projection (analytical)')
plt.subplot(132)
plt.imshow(projData3D_cut[sliceSel,:,:],vmin=0, vmax=intens_max)
plt.title('Sinogram view')
plt.subplot(133)
plt.imshow(projData3D_cut[:,:,sliceSel],vmin=0, vmax=intens_max)
plt.title('Tangentogram view')
plt.show()
#%%
def process_frames(self, data):
# print "The input data shape is", data[0].shape
if (self.out_shape_sino[1] == 1):
# create a 2D phantom
model = TomoP2D.Model(self.model, self.dims, self.path_library2D)
# create a 2D sinogram
projdata_clean = TomoP2D.ModelSino(self.model, self.dims,
self.detectors_num, self.angles,
self.path_library2D)
# Adding artifacts and noise
# forming dictionaries with artifact types
_noise_ = {
'type': self.parameters['artifacts_noise_type'],
'sigma': self.parameters['artifacts_noise_sigma'],
'seed': 0,
'prelog': False
}
# misalignment dictionary
_sinoshifts_ = {}
if self.parameters[
'artifacts_misalignment_maxamplitude'] is not None:
_sinoshifts_ = {
'maxamplitude':
self.parameters['artifacts_misalignment_maxamplitude']
}
# adding zingers and stripes
_zingers_ = {}
if self.parameters['artifacts_zingers_percentage'] is not None:
_zingers_ = {
'percentage':
self.parameters['artifacts_zingers_percentage'],
'modulus': 10
}
_stripes_ = {}
if self.parameters['artifacts_stripes_percentage'] is not None:
_stripes_ = {
'percentage':
self.parameters['artifacts_stripes_percentage'],
'maxthickness':
self.parameters['artifacts_stripes_maxthickness'],
'intensity':
self.parameters['artifacts_stripes_intensity'],
'type':
self.parameters['artifacts_stripes_type'],
'variability':
self.parameters['artifacts_stripes_variability']
}
if self.parameters[
'artifacts_misalignment_maxamplitude'] is not None:
[projdata,
shifts] = _Artifacts_(projdata_clean, _noise_, _zingers_,
_stripes_, _sinoshifts_)
else:
projdata = _Artifacts_(projdata_clean, _noise_, _zingers_,
_stripes_, _sinoshifts_)
else:
# create a 3D phantom
frame_idx = self.out_pData[0].get_current_frame_idx()[0]
model = TomoP3D.ModelSub(self.model, self.dims,
(frame_idx, frame_idx + 1),
self.path_library3D)
model = np.swapaxes(model, 0, 1)
model = np.flipud(model[:, 0, :])
# create a 3D projection data
projdata_clean = TomoP3D.ModelSinoSub(
self.model, self.dims, self.detectors_num, self.dims,
(frame_idx, frame_idx + 1), self.angles, self.path_library3D)
# Adding artifacts and noise
# forming dictionaries with artifact types
_noise_ = {
'type': self.parameters['artifacts_noise_type'],
'sigma': self.parameters['artifacts_noise_sigma'],
'seed': 0,
'prelog': False
}
# misalignment dictionary
_sinoshifts_ = {}
if self.parameters[
'artifacts_misalignment_maxamplitude'] is not None:
_sinoshifts_ = {
'maxamplitude':
self.parameters['artifacts_misalignment_maxamplitude']
}
# adding zingers and stripes
_zingers_ = {}
if self.parameters['artifacts_zingers_percentage'] is not None:
_zingers_ = {
'percentage':
self.parameters['artifacts_zingers_percentage'],
'modulus': 10
}
_stripes_ = {}
if self.parameters['artifacts_stripes_percentage'] is not None:
_stripes_ = {
'percentage':
self.parameters['artifacts_stripes_percentage'],
'maxthickness':
self.parameters['artifacts_stripes_maxthickness'],
'intensity':
self.parameters['artifacts_stripes_intensity'],
'type':
self.parameters['artifacts_stripes_type'],
'variability':
self.parameters['artifacts_stripes_variability']
}
if self.parameters[
'artifacts_misalignment_maxamplitude'] is not None:
[projdata,
shifts] = _Artifacts_(projdata_clean, _noise_, _zingers_,
_stripes_, _sinoshifts_)
else:
projdata = _Artifacts_(projdata_clean, _noise_, _zingers_,
_stripes_, _sinoshifts_)
projdata = np.swapaxes(projdata, 0, 1)
return [projdata, model]
