scholarly journals High resolution 3D-printing of trabecular bone based on micro-CT data

2014 ◽  
Vol 2 (4) ◽  
pp. 238 ◽  
Author(s):  
Volker Kuhn ◽  
Nikola Ivanovic ◽  
Wolfgang Recheis
2004 ◽  
Vol 126 (1) ◽  
pp. 122-125 ◽  
Author(s):  
Xiang Wang, ◽  
Xiangyi Liu, and ◽  
Glen L. Niebur

The Orientation of trabecular bone specimens for mechanical testing must be carefully controlled. A method for accurately preparing on-axis cylindrical specimens using high-resolution micro-CT imaging was developed. Sixteen cylindrical specimens were prepared from eight bovine tibiae. High-resolution finite element models were generated from micro-CT images of parallelepipeds and used to determine the principal material coordinate system of each parallelepiped. A cylindrical specimen was then machined with a diamond coring bit. The resulting specimens were scanned again to evaluate the orientation. The average deviation between the principal fabric orientation and the longitudinal axis of the cylindrical specimen was only 4.70±3.11°.


2000 ◽  
Vol 123 (2) ◽  
pp. 176-183 ◽  
Author(s):  
W. Pistoia ◽  
B. van Rietbergen ◽  
A. Laib ◽  
P. Ru¨egsegger

Micro-finite element (μFE) models based on high-resolution images have enabled the calculation of elastic properties of trabecular bone in vitro. Recently, techniques have been developed to image trabecular bone structure in vivo, albeit at a lesser resolution. The present work studies the usefulness of such in-vivo images for μFE analyses, by comparing their μFE results to those of models based on high-resolution micro-CT (μCT) images. Fifteen specimens obtained from human femoral heads were imaged first with a 3D-pQCT scanner at 165 μm resolution and a second time with a μCT scanner at 56 μm resolution. A third set of images with a resolution of 165 μm was created by downscaling the μCT measurements. The μFE models were created directly from these images. Orthotropic elastic properties and the average tissue von Mises stress of the specimens were calculated from six FE-analyses per specimen. The results of the 165 μm models were compared to those of the 56 μm model, which was taken as the reference model. The results calculated from the pQCT-based models, correlated excellent with those calculated from the reference model for both moduli R2>0.95 and for the average tissue von Mises stress R2>0.83. Results calculated from the downscaled micro-CT models correlated even better with those of the reference models (R2>0.99 for the moduli and R2>0.96 for the average von Mises stress). In the case of the 3D-pQCT based models, however, the slopes of the regression lines were less than one and had to be corrected. The prediction of the Poisson’s ratios was less accurate (R2>0.45 and R2>0.67) for the models based on 3D-pQCT and downscaled μCT images respectively). The fact that the results from the downscaled and original μCT images were nearly identical indicates that the need for a correction in the case of the 3D-pQCT measurements was not due to the voxel size of the images but due to a higher noise level and a lower contrast in these images, in combination with the application of a filtering procedure at 165 micron images. In summary: the results of μFE models based on in-vivo images of the 3D-pQCT can closely resemble those obtained from μFE models based on higher resolution μCT system.


2019 ◽  
Author(s):  
Thomas O’Mahoney ◽  
Lidija Mcknight ◽  
Tristan Lowe ◽  
Maria Mednikova ◽  
Jacob Dunn

AbstractSegmentation of high-resolution tomographic data is often an extremely time-consuming task and until recently, has usually relied upon researchers manually selecting materials of interest slice by slice. With the exponential rise in datasets being acquired, this is clearly not a sustainable workflow. In this paper, we apply the Trainable Weka Segmentation (a freely available plugin for the multiplatform program ImageJ) to typical datasets found in archaeological and evolutionary sciences. We demonstrate that Trainable Weka Segmentation can provide a fast and robust method for segmentation and is as effective as other leading-edge machine learning segmentation techniques.


2012 ◽  
Vol 26 (2) ◽  
pp. 302-308 ◽  
Author(s):  
Ravishankar Chityala ◽  
Sridevi Pudipeddi ◽  
Luke Arensten ◽  
Susanta Hui
Keyword(s):  
Micro Ct ◽  

Materials ◽  
2019 ◽  
Vol 12 (16) ◽  
pp. 2533 ◽  
Author(s):  
Gang-Seok Park ◽  
Seong-Kyun Kim ◽  
Seong-Joo Heo ◽  
Jai-Young Koak ◽  
Deog-Gyu Seo

The purpose of the study was to investigate the influence of 3D printing parameters on fit and internal gap of 3D printed resin dental prosthesis. The dental model was simulated and fabricated for three-unit prostheses with two implants. One hundred prostheses were 3D printed with two-layer thicknesses for five build orientations using a resin (NextDent C&B; 3D systems, Soesterberg, The Netherlands) and ten prostheses were manufactured with a milling resin as control. The prostheses were seated and scanned with micro-CT (computerized tomography). Internal gap volume (IGV) was calculated from 3D reconstructed micro-CT data. IGV, marginal fit, and lengths of internal gaps were measured, and the values were analyzed statistically. For the 3D printed prostheses, IGV was smaller at 45°, 60°, and 90° compared to other build orientations. The marginal fit evaluated by absolute marginal discrepancy was smaller than other build orientations at 45° and 60°. IGV was smaller at 50 µm layer thickness than at 100 µm layer thickness, but the marginal fit was smaller at 100 µm layer thickness than at 50 µm layer thickness. The 3D printed prosthesis had smaller internal gap than the milled prosthesis. The marginal fit of the 3D printed resin prosthesis was clinically acceptable, and build orientation of 45° and 60° would be recommended when considering fit and internal gap.


Nature ◽  
2020 ◽  
Vol 588 (7839) ◽  
pp. 594-595
Author(s):  
Cameron Darkes-Burkey ◽  
Robert F. Shepherd
Keyword(s):  

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