#-----------------------------------------------------------------------
"""
Example 09: Reconstruct data using ASTRA
========================================
"""
import foam_ct_phantom
import astra
import numpy as np
import h5py
import pylab as pl
pl.gray()
# Run 03_generate_projections_parallel.py and 04_generate_projections_cone first
projs = foam_ct_phantom.load_projections('test_projs_par.h5')
vol_geom = foam_ct_phantom.VolumeGeometry(256, 256, 256, 3 / 256)
proj_geom = foam_ct_phantom.ParallelGeometry.from_file('test_projs_par.h5')
pg = proj_geom.to_astra(single_slice=True)
vg = vol_geom.to_astra(single_slice=True)
pid = astra.create_projector('cuda', pg, vg)
w = astra.OpTomo(pid)
mid_slice = w.reconstruct('FBP_CUDA', projs[:, projs.shape[1] // 2])
pl.imshow(mid_slice)
pl.show()
infiltration_phantom = foam_ct_phantom.InfiltrationFoamPhantom(
'test_infiltration.h5')
vol_geom = foam_ct_phantom.VolumeGeometry(256, 256, 1, 3 / 256)
infiltration_phantom.generate_volume('test_infiltration_vol_start.h5',
vol_geom,
time=0)
infiltration_phantom.generate_volume('test_infiltration_vol_end.h5',
vol_geom,
time=1)
vol0 = foam_ct_phantom.load_volume('test_infiltration_vol_start.h5')
vol1 = foam_ct_phantom.load_volume('test_infiltration_vol_end.h5')
pl.imshow(vol0[0])
pl.figure()
pl.imshow(vol1[0])
pl.show()
proj_geom = foam_ct_phantom.ParallelGeometry(
256, 256, np.linspace(0, 4 * np.pi, 128, False), 3 / 256)
infiltration_phantom.generate_projections('test_infiltration_projs.h5',
proj_geom)
projs = foam_ct_phantom.load_projections('test_infiltration_projs.h5')
pl.imshow(projs[0])
pl.figure()
pl.imshow(projs[-1])
pl.show()
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")
### 08 add poisson noise
print("Adding Noise...")
fac = foam_ct_phantom.estimate_absorption_factor(prefix + 'proj_par' + suffix,
0.5)
foam_ct_phantom.apply_poisson_noise(input_file=prefix + 'proj_par' + suffix,
output_file=prefix + 'proj_noisy' + suffix,
seed=1234,
random_seed = 9876
foam_ct_phantom.ExpandingFoamPhantom.generate('test_expand.h5',
'test_phantom.h5', random_seed)
expanding_phantom = foam_ct_phantom.ExpandingFoamPhantom('test_expand.h5')
vol_geom = foam_ct_phantom.VolumeGeometry(256, 256, 1, 3 / 256)
expanding_phantom.generate_volume('test_expand_vol_start.h5', vol_geom, time=0)
expanding_phantom.generate_volume('test_expand_vol_end.h5', vol_geom, time=1)
vol0 = foam_ct_phantom.load_volume('test_expand_vol_start.h5')
vol1 = foam_ct_phantom.load_volume('test_expand_vol_end.h5')
pl.imshow(vol0[0])
pl.figure()
pl.imshow(vol1[0])
pl.show()
proj_geom = foam_ct_phantom.ParallelGeometry(
256, 128, np.linspace(0, 4 * np.pi, 128, False), 3 / 256)
expanding_phantom.generate_projections('test_expand_projs.h5', proj_geom)
projs = foam_ct_phantom.load_projections('test_expand_projs.h5')
pl.imshow(projs[0])
pl.figure()
pl.imshow(projs[-1])
pl.show()
#Author: Daniel M. Pelt #Contact: [email protected] #Website: http://dmpelt.github.io/foam_ct_phantom/ #License: MIT # #This file is part of foam_ct_phantom, a Python package for generating #foam-like phantoms for CT. #----------------------------------------------------------------------- """ Example 08: Apply Poission noise to projection data =================================================== """ import foam_ct_phantom import numpy as np import h5py import pylab as pl pl.gray() # Run 03_generate_projections_parallel.py first fac = foam_ct_phantom.estimate_absorption_factor('test_projs_par.h5', 0.5) foam_ct_phantom.apply_poisson_noise('test_projs_par.h5', 'test_projs_noisy.h5', 1234, 100, fac) projs = foam_ct_phantom.load_projections('test_projs_noisy.h5') pl.imshow(projs[0]) pl.show()
import foam_ct_phantom
import numpy as np
import h5py
import astra
import matplotlib.pylab as pl
import argparse
import os
pl.gray()
parser = argparse.ArgumentParser()
parser.add_argument("--file", required=True)
args = parser.parse_args()
projs = foam_ct_phantom.load_projections(args.file)
print(len(projs), "projections, shape", projs.shape)
pl.imshow(projs[0])
pl.title("0")
pl.show()
pl.imshow(projs[10])
pl.title("10")
pl.show()
pl.imshow(projs[20])
pl.title("20")
pl.show()
pl.gray()
random_seed = 9876
foam_ct_phantom.MovingFoamPhantom.generate('test_moving.h5', 'test_phantom.h5',
random_seed, -0.75, 0.75)
moving_phantom = foam_ct_phantom.MovingFoamPhantom('test_moving.h5')
vol_geom = foam_ct_phantom.VolumeGeometry(256, 256, 1, 3 / 256)
moving_phantom.generate_volume('test_moving_vol_start.h5', vol_geom, time=0)
moving_phantom.generate_volume('test_moving_vol_end.h5', vol_geom, time=1)
vol0 = foam_ct_phantom.load_volume('test_moving_vol_start.h5')
vol1 = foam_ct_phantom.load_volume('test_moving_vol_end.h5')
pl.imshow(vol0[0])
pl.figure()
pl.imshow(vol1[0])
pl.show()
proj_geom = foam_ct_phantom.ParallelGeometry(
256, 128, np.linspace(0, 4 * np.pi, 128, False), 3 / 256)
moving_phantom.generate_projections('test_moving_projs.h5', proj_geom)
projs = foam_ct_phantom.load_projections('test_moving_projs.h5')
pl.imshow(projs[0])
pl.figure()
pl.imshow(projs[-1])
pl.show()
