1 / 23

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

Optimization and validation of micro-CT for the characterization of non-bone porous materials. Kerckhofs Greet , Schrooten J., Van Cleynenbreugel T., Lomov SV., Wevers M. Katholieke Universiteit Leuven. Introduction. Ti bone scaffolds. HA bone scaffolds. Complex bone fractures

istas
Download Presentation

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

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Optimization and validation of micro-CT for the characterization of non-bone porous materials Kerckhofs Greet, Schrooten J., Van Cleynenbreugel T., Lomov SV., Wevers M. Katholieke Universiteit Leuven

  2. Introduction Ti bone scaffolds HA bone scaffolds Complex bone fractures • Reconstruction • Regeneration Polymer bone scaffolds

  3. Introduction • 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

  4. Introduction 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

  5. Overview • Materials • Optimisation of micro-CT • Validation of micro-CT • Work in progress

  6. Materials Ceramic bone scaffolds Metal bone scaffolds Polymeric bone scaffolds

  7. Overview • Materials • Optimisation of micro-CT • Validation of micro-CT • Work in progress

  8. µCT-simulator Micro-CT device Optimisation of the acquisition: µCT simulator Sample material Current? Voltage? Filter? Source Detector Optimal images???? Optimal images!!!! Objectively determined, ‘optimal’ acquisition parameters

  9. Spectrum Skyscan 1172 – 50kV

  10. Overview • Materials • Optimisation of micro-CT • Validation of micro-CT • Work in progress

  11. Image registration, binarization and overlay Overlay image Sliced parts Optical image Full scaffold ≠ Micro-CT scanning angle Physical slicing angle Micro-CT image interpolation Interpolated micro-CT image Micro-CT image dataset Validation: micro-CT vs. optical light microscopy Slicing Philips HOMX 161 X-ray system with AEA Tomohawk CT-software Full scaffold micro-CT dataset

  12. Experimental protocol Interpolation of the micro-CT image  Finding the corresponding micro-CT image in the dataset

  13. Image registration, binarization and overlay Overlay image Sliced parts Optical image Full scaffold ≠ Micro-CT scanning angle Physical slicing angle Micro-CT image interpolation Interpolated micro-CT image Micro-CT image dataset Validation: micro-CT vs. optical light microscopy Slicing Philips HOMX 161 X-ray system with AEA Tomohawk CT-software Full scaffold micro-CT dataset

  14. Optical image Micro-CT image Matching • Automatic image registration (F. Maes - KULeuven) • Result = overlapping binarized images • Overlap = total green / (total blue + green) • Micro-CTmismatch = total red / (total blue + green) • Opticalmismatch = total blue / (total blue + green) Micro-CT Overlap Optical

  15. Thresholding method Overlap and mismatch: influence of threshold Too high threshold Too low threshold

  16. Thresholding method Overlap and mismatch: influence of threshold 89.6 % overlap 45.1 % micro-CT mismatch 10.4 % optical mismatch Best threshold Reference threshold

  17. Results for Ti bone scaffolds 36 optical and their corresponding, interpolated micro-CT images Optimal threshold = 112

  18. Limits of the micro-CT device Limited field of view Large sample dimensions Complex structure of the sample Material of the sample Results for Ti bone scaffolds 36 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!!!!!!!

  19. Results for Ti bone scaffolds Influence of the threshold on the surface fraction (2D) Linear model predicts an increase of 2.6 % for a decrease of 5 % in threshold!!!

  20. Overview • Materials • Optimisation of micro-CT • Validation of micro-CT • Work in progress

  21. Work in progress Pixel size = 13.2 µm Micro-CT High-resolution micro-CT Optical light microscopy Pixel size = 3.7 µm

  22. Work in progress Binning on the detector Binning of the reconstructed images Changing resolution Structural analysis Changing magnification Micro-CT measurements Different device Changing threshold Cfr. Validation protocol Optical light microscopy Hg porosimetry Pore size distribution Physical measurements Structural analysis He pycnometry % open and closed porosity

  23. Thank you for your attention!!!

More Related