[Rtk-users] Issue spr/Boellaard? + First recon from raw C++ vs python

Fri Nov 5 10:30:40 EDT 2021

Dear rtk-users,

First of all a huge thanks to the developers of RTK, what a very powerful tool. Here I am am with a couple of points:

1) Boellaard scatter: after having performed multiple rtkfkd recons with different "spr" settings (from the complied C++ version), I could not find any differences between the reconstructed images. It seems like the scatter-to-primary ratio does not impact the recon. Is this to be expected/does anyone experience the same?

2) Finally I had some time to dig in the python wrapped side of RTK and run some very basic recons on Elekta raw (XVI release > 5) data - based on the FirstRecon example - for benchmarking purposes. However, I do not get to the desired result. I am pretty sure that is something quite superficial on my side, but any help is very welcome.

So the reconstruction starts from the following projections:

[cid:02b525b5-508f-4bb9-84e9-74d93726410c]
I get with the compiled version of C++

[cid:a08661fb-7c01-4e2d-be4b-3a6199642f58]
while when trying my own recon, I get

[cid:52a9a5b8-9ac8-4ad1-a591-228db1d6cedd]

To me, it seems that the geometry/axis orientation is somewhat incorrect. Trying to facilitate coming up with some suggestions, I put at the end of the mail an excerpt of the code, maybe you spot the issue right away. If you may appreciate a dataset to reproduce the problem, just let me know. Again, any suggestion is welcome, especially if a quick look from someone else may speed up things on this side.

Thank you very much in advance.

Best Regards and have a great weekend,

Matteo

  Matteo Maspero
| Clinical scientist/Postdoc
| Radiotherapy, Imaging and Cancer
| Computational Imaging Group www.compimag.org<http://www.compimag.org>
| Center for Image Sciences
| University Medical Center Utrecht
| Free on Wednesdays
| Room Q.02.2.315
| P.O. 85500
| Heidelberglaan 100, 3508 GA Utrecht, Netherlands
| E: m.maspero at umcutrecht.nl
| Tel        +31-8875 67492 / +31-614956534
| Fax       +31-8875 55850

--------------------- code excerpt ----

import sys
import os
import matplotlib.pyplot as plt
import glob
import itk
from itk import RTK as rtk
# image definition
CPUImageType = rtk.Image[itk.F, 3]

# TMP, pt_dir are the folders with the data
# Flags
Flag_saveProj = "on"

# geometry -> read xml
geometryReader = rtk.ThreeDCircularProjectionGeometryXMLFileReader.New()
geometryReader.SetFilename(TMP + "elektaGeometry")
geometryReader.GenerateOutputInformation()
geometry = geometryReader.GetGeometry()

# List of filenames
fileNames = list()
# Get list of all files in a given directory sorted by name
fileNames = sorted( filter( os.path.isfile,
                            glob.glob(pt_dir + '*his')))

projReader = rtk.ProjectionsReader[CPUImageType].New()
projReader.SetFileNames(fileNames)
projections = projReader.GetOutput()
# plot the projections
plt.subplot(1, 3, 1); plt.imshow(projections[55, :, :], cmap='gray'); plt.title('Proj X')
plt.subplot(1, 3, 2); plt.imshow(projections[:, 55, :], cmap='gray'); plt.title('Proj Y')
plt.subplot(1, 3, 3); plt.imshow(projections[:, :, 50], cmap='gray'); plt.title('Proj Z')
plt.show()

# Writer
if Flag_saveProj == "on":
    print('Writing projections image...')
    itk.imwrite(projections, TMP + 'projections.mha')
    itk.imwrite(projections, TMP + 'projections.gipl')

# Reconstruction parameter
spacingVol = [1, 1, 1]           # resolution of the recon
sizeOutputVol = [256, 256, 256]  # FOV = S ->  [270, 270, 264]
originVol = [-(sizeOutputVol[0] / 2 + 0.5) * spacingVol[0], 0., -(sizeOutputVol[2] / 2 + 0.5) * spacingVol[2]]

# Create (an empty) reconstructed image
constantImageSource = rtk.ConstantImageSource[CPUImageType].New()
constantImageSource.SetOrigin(originVol)
constantImageSource.SetSpacing(spacingVol)
constantImageSource.SetSize(sizeOutputVol)
constantImageSource.SetConstant(0.)
source = constantImageSource.GetOutput()

# FDK reconstruction
print('Reconstructing...')
FDKCPUType = rtk.FDKConeBeamReconstructionFilter[CPUImageType]
feldkamp = FDKCPUType.New()
feldkamp.SetInput(0, source)
feldkamp.SetInput(1, projections)
feldkamp.SetGeometry(geometry)
feldkamp.GetRampFilter().SetTruncationCorrection(0.0)
feldkamp.GetRampFilter().SetHannCutFrequency(0.0)
imageFDK = feldkamp.GetOutput()

# plot the reconstructed image
im = imageFDK
plt.subplot(1, 3, 1); plt.imshow(im[55, :, :], cmap='gray'); plt.title('X')
plt.subplot(1, 3, 2); plt.imshow(im[:, 55, :], cmap='gray'); plt.title('Y')
plt.subplot(1, 3, 3); plt.imshow(im[:, :, 50], cmap='gray'); plt.title('Z'); plt.show()

# Reconstruction parameter
spacingVol = [1, 1, 1]           # resolution of the recon
sizeOutputVol = [256, 256, 256]  # FOV = S ->  [270, 270, 264]
originVol = [-(sizeOutputVol[0] / 2 + 0.5) * spacingVol[0], 0., -(sizeOutputVol[2] / 2 + 0.5) * spacingVol[2]]

# Create (an empty) reconstructed image
constantImageSource = rtk.ConstantImageSource[CPUImageType].New()
constantImageSource.SetOrigin(originVol)
constantImageSource.SetSpacing(spacingVol)
constantImageSource.SetSize(sizeOutputVol)
constantImageSource.SetConstant(0.)
source = constantImageSource.GetOutput()

# FDK reconstruction
print('Reconstructing...')
FDKCPUType = rtk.FDKConeBeamReconstructionFilter[CPUImageType]
feldkamp = FDKCPUType.New()
feldkamp.SetInput(0, source)
feldkamp.SetInput(1, projections)
feldkamp.SetGeometry(geometry)
feldkamp.GetRampFilter().SetTruncationCorrection(0.0)
feldkamp.GetRampFilter().SetHannCutFrequency(0.0)
imageFDK = feldkamp.GetOutput()

# plot the reconstructed image
im = imageFDK
plt.subplot(1, 3, 1); plt.imshow(im[55, :, :], cmap='gray'); plt.title('X')
plt.subplot(1, 3, 2); plt.imshow(im[:, 55, :], cmap='gray'); plt.title('Y')
plt.subplot(1, 3, 3); plt.imshow(im[:, :, 50], cmap='gray'); plt.title('Z'); plt.show()

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