1. Recent Developments of Microtomography at GeoSoilEnviroCARS
Mark Rivers
GeoSoilEnviroCARS, Advanced Photon Source
University of Chicago

2. Outline of Talk Tomography at extreme conditions
High pressure
High speed
(High temperature, low temperature)
Recent technical developments
Reconstruction speeds
Visible light optics
Ring artifact reduction
Rotation stage imprecision

3. Absorption Tomography Setup 13-BM-D station at APS
X-ray Source
Parallel monochromatic x-rays, 8-65 keV
APS bending magnet source, 20 keV critical energy
1-50mm field of view in horizontal, up to 6 mm in vertical
Imaging System
YAG or CdWO4 single crystal scintillator
5X to 20X microscope objectives, or macro lens
1300 x 1030 pixel, 12-bit CCD camera
Data collection
Rotate sample 180 degrees, acquire images every 0.25 degrees
Data collection time: 10 minutes
Reconstruction time: 5 minutes
X-rays
Rotation stage
Sample
Scintillator
Microscope objective
CCD camera
Visible light

4. Differential Absorption Tomography Clint Willson (Louisiana State University)
8mm diameter sand column with aqueous phase containing Cs and organic phase containing I.
32.5 keV, below I and Cs K absorption edges
33.2 keV, above I and below Cs K absorption edges
36.0 keV, above I and Cs K absorption edges
keV, showing distribution of I in the organic phase
, showing distribution of Cs in the aqueous phase

5. High-P tomography: Instrumentation
Die set
Harmonic
Drive
Transport
Rails
250 T press frame
Hydraulic
ram
Thrust bearings
Max. load 50 tons

6. High pressure tomography: setup Current pressure maxium=10GPa (100 kbar) Goal: 20 GPa (200 kbar)
Fe – S alloy
Top view
CCD detector
Al2O3
Microscope objective
Phosphor
(YAG)
Monochromator
Mirror
Sample
Rotation
Drickamer
Incident X-rays
(white)
Visible light
Transmitted X-rays
Monochromatic beam

7. 803 µm vitreous forsterite sphere
Anvil BE BN
Fe0.9S0.1
0 tons
Gaudio, Lesher, Wang, Nishiyama

9. High-Speed Radiography of Granular Particle Jets John Royer, University of Chicago Physics Dept.
Sphere falling into a granular particle (e.g. sand) bed produces a jet
These images are above the surface, done with visible light
1 atmosphere
Reduced pressure

10. Want to understand what is happening below the surface
Used “pink” x-ray beam, high speed radiography
100 msec exposure time, 5000 frames/sec

11. Processing Times
Data processing is done in 2 steps using IDL graphical user-interface
Pre-processing: dark current and flat field normalization, zinger removal
Sinogram calculation and reconstuction
Reconstruction is done with Gridrec FFT-based C code from Brookhaven.
No measureable difference from FBP, but >15X faster.
Recently changed from Intel MKL or Numerical Recipes FFT to the FFTW package times faster.
Upgraded to dual 3.4 GHz Intel, 8GB RAM, 64-bit Linux, 64-bit IDL,
FFTW is built single-threaded, second CPU is idle for other tasks
Columns
Slices
Projections
Preprocessing
time for volume
Sinogram
time per
slice
Recon. time per slice
Recon. time for volume
650
515
720 30
0.11
0.19
170
1024
105
0.17
0.58
774
1300
1030
900
200
0.25
0.62

12. Optics Improvements Sand and fluid, 33.269 keV, Z slice
We have been using Mitutoyu long working distance microscope objectives with various tube lens to achieve the desired fields of view. This often involved shorter tube lens than the nominal 200mm tube length.
Recently purchased a Nikon macro lens. This lens allows various fields of view, depending on how the lens is focus, and what extension tubes if any are used.
We have now compared images collected with very similar pixel sizes using the Mitutoyu lenses and the Nikon lens. It is clear that at least at fields of view > 6mm the Nikon lens is significantly sharper.
Sand and fluid, keV, Z slice
Mitutoyu 5X, 17.5mm tube, 11.1 micron pixels
Nikon lens, PK-11A extender, 11.2 micron pixels

13. Another example of improvement in optics
Meteorite, 38 keV, Y slices
Mitutoyu 5X, 17.5mm tube, 11.1 micron pixels
Nikon lens, PK-11A extender, 11.2 micron pixels

14. Ring Artifact Reduction - Algorithm
Compute average of all rows in sinogram
This should be a smooth function with little high-frequency content
Compute a smoothed version of the average with user-selectable smoothing width.
Unsmoothed version minus smoothed version is the correction factor for that pixel
Subtract the correction from that pixel in every projection

15. Ring Artifact Reduction - Sinograms
Sinogram before correction
Sinogram after correction with 21-point smoothing

16. Ring Artifact Reduction - Reconstructions
No correction
9-point smooth
21-point smooth

17. Ring Artifacts – A Puzzle
We often found ring artifacts even after applying the preceeding algorithm
Ring artifact suppression=Off
Ring artifact suppression=9 point

18. Ring Artifacts – the Flat Field Problem
We finally realized that these rings were arising from the flat fields
This image was reconstructed simply assuming a constant flat field of 4000 counts! Many fewer rings!
Ring artifact suppression=Off
Ring artifact suppression=9 point

19. Ring Artifacts – Major Improvement
We were previously interpolating the flat fields with time to best estimate the flat field when each projection was taken
This introduced 2 serious problems:
Noise in the flat field images resulted in anomalous pixels (rings) in many projections
The resulting “rings” were only partial rings, not semi-circles, because each noisy pixel was only used over an angular range of degrees.
This greatly reduced the efficacy of the ring artifact reduction algorithm
Solution was easy:
Average all the flat fields, rather than interpolating them
Better solution would be to collect many flat fields periodically, then average and interpolate

20. Ring Artifacts – Using Flat Field Averaging
Ring artifact suppression=Off
Ring artifact suppression=9 point

21. Ring Artifacts – Another Example
Old default, flat field interpolation, 9-point smooth for reduction
New default, flat field averaging, 9-point smooth for reduction

22. Rotation Stage Imperfections
When doing high-resolution tomography we have seen small horizontal shifts in the sinogram at some angles.
This is due to mechanical imprecision (eccentricity, wobble) in the stage
Sinogram with small horizontal shifts at some angles
Enlargement of lower right, showing shifts more prominently

23. Rotation Stage Corrections
Developed an algorithm to correct these shifts using only the sinogram data itself.
The center of gravity of each row of the sinogram (average of horizontal distance X –log(I/I0)) itself must describe a sine wave
Fit the sine wave to the center of gravity for the sinogram of each slice. Measure the deviation from the best-fit sine wave
Some of that deviation is noise, some is systematic error due to mechanical shifts in the stage
The mechanical shifts should be the same for every slice, thus we can reduce noise by averaging over all slices
Must reject slices with no meaningful center-of-gravity, i.e. slices with just air or with complete absorption

24. Rotation Stage Corrections

25. Rotation Stage Corrections - Sinograms
Enlargement of sinogram before correction
Enlargement of sinogram after correction

26. Rotation Stage Corrections - Reconstructions
Reconstruction before correction
Reconstruction after correction

27. Rotation Stage Corrections - Reconstructions
Enlargement of reconstruction before correction
Enlargement of reconstruction after correction

28. Rotation Stage Corrections – Laser Autocollimator Measurements
Used Newport LAE500 laser autocollimator with high-precision reflective ball to measure rotation motion in horizontal and vertical
Mounted ball near center of rotation, fit sine-wave for expected motion
Deviations from sine-wave are errors in horizontal and vertical

29. Laser Autocollimator Measurements Old Newport URM-80 Stage

30. Laser Autocollimator Measurements New Newport URM-80 Stage

31. Rotation Stage Corrections – Conclusions
Software can automatically correct for rotation axis imperfection
Our stage was particularly bad at ~3-4 microns, but as resolution is pushed to sub-micron tomography there will be a real benefit from these corrections
Laser autocollimator is very useful for evaluating stages