def generate_phantom(porosity, noise_parameter, threshold_levels=None):
print(f'Porosity: {porosity:.2f}')
print(f'Noise parameter: {noise_parameter}')
phantom = avg.blobs(shape=shape, porosity=porosity, random_seed=random_seed)
print(f'Generated porosity: {1 - np.sum(phantom)/phantom.size:.2f}')
phantom[helper.get_floating_solids(phantom)] = False
helper.show_2d_sections(phantom, x=x_slice, y=y_slice, z=z_slice)
phantom_recon = moe.process_image(
phantom,
number_of_angles,
reconstruct_filter='ramp',
noise_parameter=noise_parameter,
noise_method=noise_method,
source_blurring=source_blurring,
detector_blurring=detector_blurring
)
helper.show_2d_sections(phantom_recon, x=x_slice, y=y_slice, z=z_slice)
# plt.figure(figsize=(20, 20))
# plt.imshow(phantom_recon[0, :, :], cmap='gray')
phantom_recon -= np.min(phantom_recon)
phantom_recon /= np.max(phantom_recon)
phantom_recon = (phantom_recon * 255).astype(np.uint8)
phantom_recon_bin, otsu_level = helper.binarize_image(phantom_recon)
helper.show_2d_sections(phantom_recon_bin, x=x_slice, y=y_slice, z=z_slice)
recon_bin_porosity = 1 - np.sum(phantom_recon_bin)/phantom_recon_bin.size
show_phantoms_stats(phantom, phantom_recon, otsu_level)
floating_solids = helper.get_floating_solids(phantom_recon_bin)
closed_pores = helper.get_closed_pores(phantom_recon_bin)
floating_solids_count = np.sum(floating_solids)
closed_pores_count = np.sum(closed_pores)
print(f'Floating solids: {floating_solids_count}')
print(f'Closed pores: {closed_pores_count}')
print('\n')
if threshold_levels is not None:
for threshold_level in threshold_levels:
phantom_recon_bin[phantom_recon < threshold_level] = False
phantom_recon_bin[phantom_recon >= threshold_level] = True
helper.show_2d_sections(phantom_recon_bin, x=x_slice, y=y_slice, z=z_slice)
floating_solids = helper.get_floating_solids(phantom_recon_bin)
closed_pores = helper.get_closed_pores(phantom_recon_bin)
print(f'Threshold level: {threshold_level}')
print(f'Binarized porosity: {1 - np.sum(phantom_recon_bin)/phantom_recon_bin.size:.2f}')
print(f'Floating solids: {np.sum(floating_solids)}')
print(f'Closed pores: {np.sum(closed_pores)}')
print('\n')
plt.show()
return recon_bin_porosity, floating_solids_count, closed_pores_count
import helper
import anisotropic_volume_generator as avg
import model_of_experiment as moe
from scipy import ndimage
# %%
recalculate = False
# %%
sample = helper.get_data_from_file(
'/Users/grimax/Desktop/tmp/porous sample/sample.h5', 'Reconstruction')
bin_sample_path = '/Users/grimax/Desktop/tmp/porous sample/bin_sample.h5'
if recalculate:
bin_sample = helper.binarize_image(sample)
helper.save_data_to_file(bin_sample_path, 'Binarized', bin_sample)
bin_sample = helper.get_data_from_file(bin_sample_path, 'Binarized', 'bool')
porosity = helper.calc_porosity(bin_sample)
bin_sample_filled = helper.fill_floating_solids_and_closed_pores(bin_sample)
helper.calc_porosity(bin_sample_filled)
sample_filtered_path = '/Users/grimax/Desktop/tmp/porous sample/sample_filtered.h5'
if recalculate:
sample_filtered = helper.filter_image(sample, 9)
helper.save_data_to_file(sample_filtered_path, 'Filtered', sample_filtered)
# %%
phantom_recon_180_sart_noise_30)
recon_blurring_shape, recon_blurring_min, recon_blurring_max, recon_blurring_mean, recon_blurring_std = helper.get_stats(
phantom_recon_180_hamming_noise_30_blurring)
recon_blurring_sart_shape, recon_blurring_sart_min, recon_blurring_sart_max, recon_blurring_sart_mean, recon_blurring_sart_std = helper.get_stats(
phantom_recon_180_sart_noise_30_blurring)
# %%
helper.plot_column(phantom_recon_180_hamming_noise_30)
helper.plot_column(phantom_recon_180_sart_noise_30)
helper.plot_column(phantom_recon_180_hamming_noise_30_blurring)
helper.plot_column(phantom_recon_180_sart_noise_30_blurring)
# %%
bin_recon = helper.binarize_image(phantom_recon_180_hamming_noise_30)
bin_recon_sart = helper.binarize_image(phantom_recon_180_sart_noise_30)
bin_recon_blurring = helper.binarize_image(
phantom_recon_180_hamming_noise_30_blurring)
bin_recon_blurring_sart = helper.binarize_image(
phantom_recon_180_sart_noise_30_blurring)
# %%
helper.show_2d_sections(bin_recon, x=x_slice, y=y_slice, z=z_slice)
helper.show_2d_sections(bin_recon_sart, x=x_slice, y=y_slice, z=z_slice)
helper.show_2d_sections(bin_recon_blurring, x=x_slice, y=y_slice, z=z_slice)
helper.show_2d_sections(bin_recon_blurring_sart,
x=x_slice,
y=y_slice,
max_v = 2**bits
data_int = helper.image_digitize(data, bits)
# %% id="Ij2yrjqCyJZ1" colab_type="code" colab={"base_uri": "https://localhost:8080/", "height": 34} outputId="10c0e1d6-e287-4e19-b6c5-db169460dbcf"
with h5py.File(f'{file_dir}sample_int.h5', mode='w') as file_to_save:
file_to_save.create_dataset('Reconstruction',
data=data_int,
compression='lzf')
# %% id="Tlan_ddGy4JE" colab_type="code" colab={"base_uri": "https://localhost:8080/", "height": 611} outputId="0b4c5713-3ff9-4a19-8bef-fafe347e9325"
plt.figure(figsize=(5, 5))
plt.imshow(data_int[:, :, 0])
plt.colorbar()
# %%
data_bin, _ = helper.binarize_image(data_int)
plt.figure(figsize=(5, 5))
plt.imshow(data_bin[:, :, 0])
# %%
data_bin_erosion = helper.erosion(data_bin)
data_bin_dilation = helper.dilation(data_bin)
data_bin_edges = np.ones(
data_bin.shape) - data_bin_erosion - ~data_bin_dilation
fig, axes = plt.subplots(1, 3, figsize=(15, 5))
axes[0].imshow(data_bin_erosion[:, :, 0])
axes[1].imshow(data_bin_dilation[:, :, 0])
axes[2].imshow(data_bin_edges[:, :, 0])
# %%
noise_parameter=30,
noise_method='poisson',
detector_blurring=True)
phantom_recon_shape, phantom_recon_min, phantom_recon_max, phantom_recon_mean, phantom_recon_std = helper.get_stats(
phantom_recon)
helper.show_2d_sections(phantom_recon, x=x_slice, y=y_slice, z=z_slice)
helper.show_histogram(phantom_recon,
xmin=phantom_recon_min,
xmax=phantom_recon_max,
log=True)
# %%
helper.scatter_plot(phantom_recon, phantom, 'phantom_recon vs phantom')
# %%
phantom_recon_bin, _ = helper.binarize_image(phantom_recon)
floating_solids = helper.get_floating_solids(phantom_recon_bin)
print(f'Floating solids: {np.sum(floating_solids)}')
# helper.show_2d_sections(phantom_recon_bin, x=x_slice, y=y_slice, z=z_slice)
# %%
helper.scatter_plot(phantom_recon, phantom_recon_bin,
'phantom_recon vs phantom_recon_bin')
# %%
phantom_recon_bin_filled = helper.fill_floating_solids_and_closed_pores(
phantom_recon_bin)
floating_solids_bin_filled = helper.get_floating_solids(
phantom_recon_bin_filled)
print(f'Floating solids: {np.sum(floating_solids_bin_filled)}')