# Reconstruction with TomoPy¶

Here is an example of how to use the gridrec [B5] reconstruction algorithm with TomoPy [A1].

First install TomoPy.

[1]:

import tomopy


Tomographic data input in TomoPy is supported by DXchange.

[2]:

import dxchange


Matplotlib provides plotting of the result in this notebook. Paraview or other tools are available for more sophisticated 3D rendering.

[3]:

import matplotlib.pyplot as plt


Import and activate Python’s built in logging module if desired. It may print something helpful.

[4]:

import logging
logging.basicConfig(level=logging.INFO)


This data set file format follows the APS beamline 2-BM and 32-ID data-exchange definition. Other file format readers for other synchrotrons are also available with DXchange.

[5]:

proj, flat, dark, theta = dxchange.read_aps_32id(
fname='../../../source/tomopy/data/tooth.h5',
sino=(0, 2),  # Select the sinogram range to reconstruct.
)

INFO:dxchange.reader:Data successfully imported: /home/dching/Documents/tomopy/source/tomopy/data/tooth.h5


Plot the sinogram

[6]:

plt.imshow(proj[:, 0, :])
plt.show()


If the angular information is not avaialable from the raw data you need to set the data collection angles. In this case, theta is set as equally spaced between 0-180 degrees.

[7]:

if theta is None:
theta = tomopy.angles(proj.shape[0])


Perform the flat-field correction of raw data:

$\frac{proj - dark} {flat - dark}$
[8]:

proj = tomopy.normalize(proj, flat, dark)


Calculate $-log(proj)$ to linearize transmission tomography data.

[9]:

proj = tomopy.minus_log(proj)


Tomopy provides various methods ([B12], [B25], [B16]) to find the rotation center.

[10]:

rot_center = tomopy.find_center(proj, theta, init=290, ind=0, tol=0.5)

INFO:tomopy.recon.rotation:Trying rotation center: [290.]
INFO:tomopy.recon.rotation:Function value = 2.014651
INFO:tomopy.recon.rotation:Trying rotation center: [304.5]

Reconstructing 1 slice groups with 1 master threads...
Reconstructing 1 slice groups with 1 master threads...
Reconstructing 1 slice groups with 1 master threads...

INFO:tomopy.recon.rotation:Function value = 2.076837
INFO:tomopy.recon.rotation:Trying rotation center: [275.5]
INFO:tomopy.recon.rotation:Function value = 2.259117
INFO:tomopy.recon.rotation:Trying rotation center: [297.25]
INFO:tomopy.recon.rotation:Function value = 1.920647
INFO:tomopy.recon.rotation:Trying rotation center: [304.5]

Reconstructing 1 slice groups with 1 master threads...
Reconstructing 1 slice groups with 1 master threads...
Reconstructing 1 slice groups with 1 master threads...

INFO:tomopy.recon.rotation:Function value = 2.076837
INFO:tomopy.recon.rotation:Trying rotation center: [293.625]
INFO:tomopy.recon.rotation:Function value = 1.939667
INFO:tomopy.recon.rotation:Trying rotation center: [300.875]
INFO:tomopy.recon.rotation:Function value = 1.997986
INFO:tomopy.recon.rotation:Trying rotation center: [295.4375]

Reconstructing 1 slice groups with 1 master threads...
Reconstructing 1 slice groups with 1 master threads...
Reconstructing 1 slice groups with 1 master threads...

INFO:tomopy.recon.rotation:Function value = 1.908336
INFO:tomopy.recon.rotation:Trying rotation center: [293.625]
INFO:tomopy.recon.rotation:Function value = 1.939667
INFO:tomopy.recon.rotation:Trying rotation center: [296.34375]
INFO:tomopy.recon.rotation:Function value = 1.906685
INFO:tomopy.recon.rotation:Trying rotation center: [297.25]

Reconstructing 1 slice groups with 1 master threads...
Reconstructing 1 slice groups with 1 master threads...
Reconstructing 1 slice groups with 1 master threads...

INFO:tomopy.recon.rotation:Function value = 1.920647
INFO:tomopy.recon.rotation:Trying rotation center: [295.890625]
INFO:tomopy.recon.rotation:Function value = 1.906942

Reconstructing 1 slice groups with 1 master threads...


Reconstruct using the gridrec algorithm. Tomopy provides various reconstruction and provides wrappers for other libraries such as the ASTRA toolbox.

[11]:

recon = tomopy.recon(proj, theta, center=rot_center, algorithm='gridrec', sinogram_order=False)

Reconstructing 2 slice groups with 2 master threads...


Mask each reconstructed slice with a circle.

[12]:

recon = tomopy.circ_mask(recon, axis=0, ratio=0.95)

[13]:

plt.imshow(recon[0, :, :])
plt.show()

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