department of metallurgy and materials engineering materials performance and non-destructive testing...

Department of Metallurgy and Materials Engineering

Materials Performance and Non-Destructive Testing

Optimization and validation of micro-CT Optimization and validation of micro-CT for the characterization of for the characterization of non-bone porous materialsnon-bone porous materials

Kerckhofs Greet, Schrooten J., Van Cleynenbreugel T., Lomov SV., Wevers M.

Katholieke Universiteit Leuven

-2-Department of Metallurgy and Materials Engineering Micro-CT symposium – 31st May 2007


IntroductionIntroduction

Complex bone fractures• Reconstruction

• Regeneration

Ti bone scaffolds

HA bone scaffolds

Polymer bone scaffolds




• Bone scaffolds design: pore size between 40 en 200µm, mechanical properties(stress and strain), biocompatibility, etc.

• For quantifying the microstructure and the mechanical properties of bone scaffolds in a non-destructive way = high throughput screening of the design Micro-CT




Current problems with micro-CT: - Acquisition parameters by ‘trial and error’

- No quantitative validation criteria for non-bone porous materials

- No protocol for image processing and analysis

Experimental protocol for the

optimisation and validation of micro-CT



OverviewOverview

Materials

Optimisation of micro-CT

Validation of micro-CT

Work in progress



MaterialsMaterials

Metal bone scaffolds

Ceramic bone scaffolds

Polymeric bone scaffolds



OverviewOverview

Materials



Work in progress



Optimisation of the acquisition: µCT simulatorOptimisation of the acquisition: µCT simulator

Micro-CT device

Voltage?Current?

Filter?

Optimal images????

µCT-simulator

DetectorSample material

Source

Objectively determined, ‘optimal’ acquisition parameters

Optimal images!!!!



0

1000

2000

3000

4000

5000

6000

0 5 10 15 20 25 30 35 40 45 50

Photon Energy (keV)

Nu

mb

er o

f p

ho

ton

s (c

ou

nts

)

50kV_No Filter

50kV_Al 0.5mm

50kV_Al 1mm

50kV_AlCu

Spectrum Skyscan 1172 – 50kVSpectrum Skyscan 1172 – 50kV



OverviewOverview

Materials



Work in progress



Full scaffold

Philips HOMX 161 X-raysystem with AEATomohawk CT-software

Full scaffoldmicro-CT dataset

Sliced partsSlicing Image

registration, binarizationand overlay

Optical image

Validation: micro-CT vs. optical light microscopyValidation: micro-CT vs. optical light microscopy

Interpolated micro-CT image

Micro-CT image interpolation

Physical slicing angle

Micro-CT scanning angle≠

Micro-CT image dataset

Overlay

image



Experimental protocolExperimental protocol

Interpolation of the micro-CT image Finding the corresponding micro-CT image in the dataset



Full scaffold

Philips HOMX 161 X-raysystem with AEATomohawk CT-software

Full scaffoldmicro-CT dataset

Sliced partsSlicing Image

registration, binarizationand overlay

Optical image

Validation: micro-CT vs. optical light microscopyValidation: micro-CT vs. optical light microscopy

Interpolated micro-CT image

Micro-CT image interpolation

Physical slicing angle

Micro-CT scanning angle≠

Micro-CT image dataset

Overlay

image



• Automatic image registration (F. Maes - KULeuven)• Result = overlapping binarized images

• Overlap = total green / (total blue + green)• Micro-CT mismatch = total red / (total blue + green)• Optical mismatch = total blue / (total blue + green)

MatchingMatching

Optical

Micro-CT imageOptical image

Micro-CTOverlap



Thresholding methodThresholding methodOverlap and mismatch: influence of threshold

•

Too high threshold Too low threshold



Thresholding methodThresholding methodOverlap and mismatch: influence of threshold

Optimal threshold

0%

10%

20%30%

40%

50%

60%

70%80%

90%

100%

77 82 87 92 97 102 107 112 117 122 127

Threshold

Perc

enta

ge o

verl

ap &

m

ismat

ch

-5%

0%

5%

10%

15%

20%

25%

30%

35%

40%

Overlap - total m

ismatch

Overlap

µCT mismatch

Optical mismatch

Total mismatch

Overlap minus total mismatch

Best threshold

89.6 % overlap

45.1 % micro-CT mismatch

10.4 % optical mismatchReference threshold



Results for Ti bone scaffoldsResults for Ti bone scaffolds36 optical and their corresponding, interpolated micro-CT images

Optimal threshold = 112



Results for Ti bone scaffoldsResults for Ti bone scaffolds36 optical and their corresponding, interpolated micro-CT images

82.7 ± 4.54 % mean overlap

43.8 ± 9.63 % micro-CT mismatch

17.3 ± 4.39 % optical mismatch

AND…

… influence of the threshold is significant!!!!!!!

Limits of the micro-CT device

Limited field of viewLarge sample dimensions

Complex structure of the sample

Material of the sample

+



Results for Ti bone scaffoldsResults for Ti bone scaffoldsInfluence of the threshold on the surface fraction (2D)

Linear model predicts an increase of 2.6 % for a decrease of 5 % in threshold!!!

y = -0.53x + 16.6

R2 = 0.73

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

Proportional decrease in threshold (% )

Surf

ace

frac

tion

-mic

ro-C

T (%

)

0

10

20

30

40

50

60

-40-35-30-25-20-15-10-50

Percentage increase in Sm

icro-CT

per 5%

decrease in threshold (%)

Surface Fraction Micro-CT (Smicro-CT)

Percentage increase in Smicro-CT per 5%increase in threshold-average values

Percentage increase in Smicro-CT per 5%increase in threshold-linear model

Linear model



OverviewOverview

Materials



Work in progress



Work in progressWork in progress

Pixel size = 13.2 µm Pixel size = 3.7 µm

Optical light microscopy

Micro-CT High-resolution micro-CT



Work in progressWork in progress

Physical measurements

Micro-CT measurements

Changing resolution

Changing threshold

He pycnometry

Hg porosimetry

Structural analysis

Structural analysis

Optical light microscopy

Binning on the detector

Binning of the reconstructed images

Changing magnification

Cfr. Validation protocol

Different device

Pore size distribution

% open and closed porosity



Thank you for your attention!!!

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