def create_ct_foam_phantom(shape=501, seed=0, gen_new=False):
""""""
if gen_new:
foam_ct_phantom.FoamPhantom.generate('large_foam_phantom.h5',
seed,
nspheres_per_unit=10000)
# (nx, ny, nx) for phatom volume geometry
shape = shape if isinstance(shape, tuple) else (shape, ) * 3
phantom = foam_ct_phantom.FoamPhantom('large_foam_phantom.h5')
geom = foam_ct_phantom.VolumeGeometry(*shape, voxsize=3 / shape[0])
phantom.generate_volume('test_phantom.h5', geom)
# [z,y,x] axis order
phantom_volume = foam_ct_phantom.load_volume('test_phantom.h5')
return phantom_volume
#
#This file is part of foam_ct_phantom, a Python package for generating
#foam-like phantoms for CT.
#-----------------------------------------------------------------------
"""
Example 04: Generate cone-beam projections
==========================================
"""
import foam_ct_phantom
import numpy as np
import h5py
import pylab as pl
pl.gray()
phantom = foam_ct_phantom.FoamPhantom('test_phantom.h5')
geom = foam_ct_phantom.ConeGeometry(256,
256,
np.linspace(0, 2 * np.pi, 256),
3 / 256,
sod=2,
odd=0,
usecuda=False)
phantom.generate_projections('test_projs_cone.h5', geom)
projs = foam_ct_phantom.load_projections('test_projs_cone.h5')
pl.imshow(projs[0])
pl.show()
def build_foam_phantom_dataset(folder_path,
n_phantoms,
spheres_per_unit=10000,
GPU_ID=0):
# Choose to reset dataset path or not
if os.path.exists(folder_path):
print("Path already exists, delete?")
choice = input()
if choice.lower()[0] == 'y':
shutil.rmtree(folder_path)
os.makedirs(folder_path)
else:
print("Will overwrite files in folder")
shape = (501, ) * 3
n_rad_slices = 360
temp_dir = '_temp_phatoms/'
if not os.path.exists(temp_dir):
os.mkdir(temp_dir)
scanner_params = FleX_ray_scanner()
orbit_elevation = [-15, 0, 15]
theta_range = np.linspace(0, np.pi, n_rad_slices, endpoint=False)
for i in range(n_phantoms):
foam_ct_phantom.FoamPhantom.generate(
os.path.join(temp_dir, 'foam_phantom.h5'),
seed=i,
nspheres_per_unit=spheres_per_unit)
phantom = foam_ct_phantom.FoamPhantom(
os.path.join(temp_dir, 'foam_phantom.h5'))
geom = foam_ct_phantom.VolumeGeometry(*shape, voxsize=3 / shape[0])
phantom.generate_volume(os.path.join(temp_dir, 'gen_phantom.h5'), geom)
phantom_volume = foam_ct_phantom.load_volume(
os.path.join(temp_dir, 'gen_phantom.h5'))
if not os.path.exists(os.path.join(folder_path, f'phantom{i+1}/')):
os.makedirs(os.path.join(folder_path, f'phantom{i+1}/'))
rad_slices = astra_sim.radial_slice_sampling(phantom_volume,
theta_range)
for j in range(len(rad_slices)):
print(f"\rSaving phantom_n{i+1:0>3d}_s{j+1:0>4d}.tif", end=' ' * 5)
imsave(
os.path.join(folder_path, f'phantom{i+1}/',
f"phantom_true_n{i+1:0>3d}_s{j+1:0>4d}.tif"),
rad_slices[j].astype('float32'))
print('')
# Simulates FDK reconstruction for all 3 orbits
for orbit in [1, 2, 3]:
vecs = astra_sim.create_scan_geometry(
scanner_params, 1200, elevation=orbit_elevation[orbit - 1])
projections = astra_sim.create_CB_projection(phantom_volume,
scanner_params,
proj_vecs=vecs,
gpu_id=GPU_ID)
fdk_phantom_volume = astra_sim.FDK_reconstruction(projections,
scanner_params,
proj_vecs=vecs,
gpu_id=GPU_ID,
rec_shape=(501,
501,
501))
fdk_rad_slices = astra_sim.radial_slice_sampling(
fdk_phantom_volume, theta_range)
for j in range(len(rad_slices)):
print(f"\rSaving phantom_n{i+1:0>3d}_s{j+1:0>4d}.tif",
end=' ' * 5)
imsave(
os.path.join(
folder_path, f'phantom{i+1}/',
f"phantom_fdk_n{i+1:0>3d}_o{orbit:d}_s{j+1:0>4d}.tif"),
fdk_rad_slices[j].astype('float32'))
print('')
# Removes temp phatom files
shutil.rmtree(temp_dir)
else:
random_seed = int(args.seed)
prefix = "data/" + str(random_seed) + "_"
suffix = "_" + str(args.spheres) + "spheres.h5"
# Note that nspheres_per_unit is set to a low value to reduce the computation time here.
# The default value is 100000.
foam_ct_phantom.FoamPhantom.generate(prefix + 'phantom' + suffix,
random_seed,
nspheres_per_unit=args.spheres)
### 03 create parallel projection
print("Projecting...")
phantom = foam_ct_phantom.FoamPhantom(prefix + 'phantom' + suffix)
geom = foam_ct_phantom.ParallelGeometry(256, 256,
np.linspace(0, np.pi, 128, False),
3 / 256)
phantom.generate_projections(prefix + 'proj_par' + suffix, geom)
projs = foam_ct_phantom.load_projections(prefix + 'proj_par' + suffix)
print(len(projs), "projections, shape", projs.shape)
pl.imshow(projs[0])
pl.savefig("projected.png")
pl.imshow(projs[3])
pl.savefig("projected3.png")