Application of the scaling index method to μCT images of human trabecular bone for the characterization of biomechanical strength

Author(s):  
Roberto A. Monetti ◽  
Jan Bauer ◽  
Dirk Müller ◽  
Ernst Rummeny ◽  
Maiko Matsuura ◽  
...  
2015 ◽  
Vol 137 (1) ◽  
Author(s):  
Alexander Zwahlen ◽  
David Christen ◽  
Davide Ruffoni ◽  
Philipp Schneider ◽  
Werner Schmölz ◽  
...  

The local interpretation of microfinite element (μFE) simulations plays a pivotal role for studying bone structure–function relationships such as failure processes and bone remodeling. In the past μFE simulations have been successfully validated on the apparent level, however, at the tissue level validations are sparse and less promising. Furthermore, intratrabecular heterogeneity of the material properties has been shown by experimental studies. We proposed an inverse μFE algorithm that iteratively changes the tissue level Young’s moduli such that the μFE simulation matches the experimental strain measurements. The algorithm is setup as a feedback loop where the modulus is iteratively adapted until the simulated strain matches the experimental strain. The experimental strain of human trabecular bone specimens was calculated from time-lapsed images that were gained by combining mechanical testing and synchrotron radiation microcomputed tomography (SRμCT). The inverse μFE algorithm was able to iterate the heterogeneous distribution of moduli such that the resulting μFE simulations matched artificially generated and experimentally measured strains.


2011 ◽  
Vol 2011 ◽  
pp. 1-21 ◽  
Author(s):  
G. Rossmanith ◽  
H. Modest ◽  
C. Räth ◽  
A. J. Banday ◽  
K. M. Górski ◽  
...  

In the recent years, non-Gaussianity and statistical isotropy of the Cosmic Microwave Background (CMB) was investigated with various statistical measures, first and foremost by means of the measurements of the WMAP satellite. In this paper, we focus on the analyses that were accomplished with a measure of local type, the so-calledScaling Index Method(SIM). The SIM is able to detect structural characteristics of a given data set and has proven to be highly valuable in CMB analysis. It was used for comparing the data set with simulations as well as surrogates, which are full-sky maps generated by randomisation of previously selected features of the original map. During these investigations, strong evidence for non-Gaussianities as well as asymmetries and local features could be detected. In combination with the surrogates approach, the SIM detected the highest significances for non-Gaussianity to date.


2001 ◽  
Vol 86 (1-2) ◽  
pp. 241-246 ◽  
Author(s):  
F Jamitzky ◽  
R.W Stark ◽  
W Bunk ◽  
S Thalhammer ◽  
C Räth ◽  
...  

2011 ◽  
Author(s):  
John Jameson ◽  
Carolyne Albert ◽  
Peter Smith ◽  
Robert Molthen ◽  
Gerald Harris

Stem Cells ◽  
2003 ◽  
Vol 21 (6) ◽  
pp. 681-693 ◽  
Author(s):  
Richard Tuli ◽  
Suraj Tuli ◽  
Sumon Nandi ◽  
Mark L. Wang ◽  
Peter G. Alexander ◽  
...  

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