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A bone sample containing a bone graft substitute analyzed by correlating density information obtained by X-ray micro tomography with compositional information obtained by Raman microscopy
VerfasserCharwat-Pessler, Johann ; Musso, Maurizio In der Gemeinsamen Normdatei der DNB nachschlagen ; Petutschnigg, Alexander ; Entacher, Karl ; Plank, Bernhard ; Wernersson, Erik ; Tangl, Stefan ; Schuller-Götzburg, Peter
Erschienen in
Materials, Basel, 2015, Jg. 2015, H. 8, S. 3831-3853
ErschienenMDPI, 2015
SpracheEnglisch
DokumenttypAufsatz in einer Zeitschrift
Schlagwörter (EN)X-ray micro computed tomography / Raman spectroscopy / bone / Bio-Oss® cluster analysis / image segmentation
ISSN1996-1944
URNurn:nbn:at:at-ubs:3-3596 Persistent Identifier (URN)
DOI10.3390/ma8073831 
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A bone sample containing a bone graft substitute analyzed by correlating density information obtained by X-ray micro tomography with compositional information obtained by Raman microscopy [3.83 mb]
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Zusammenfassung (Englisch)

The ability ofbonegraft substitutes to promote newbone formation has been increasingly used in the medical field to repair skeletal defects or to replace missingbonein a broad range of applications in dentistry and orthopedics. A common way to assess such materials is via micro computed tomography (-CT), through the density information content provided by the absorption of X-rays. Information on the chemical composition of a material can be obtained via Raman spectroscopy. By investigating abonesamplefrom miniature pigs containing thebonegraft substitute Bio Oss®, we pursued the target of assessing to what extent the density information gained by -CT imaging matches the chemical information content provided by Raman spectroscopic imaging. Raman images and Raman correlation maps of the investigatedsamplewere used in order to generate a Raman based segmented image by means of an agglomerative, hierarchical cluster analysis. The resulting segments, showing chemically related areas, were subsequently compared with the -CT image by means of a one-way ANOVA. We found out that to a certain extent typical gray-level values (and the related histograms) in the -CT image can be reliably related to specific segments within the image resulting from the cluster analysis.

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