Add like
Add dislike
Add to saved papers

Segmentation Methods for Micro CT Images: A Comparative Study Using Human Bone Samples.

X-ray microtomography (microCT) is a nondestructive technique used to assess bone morphometry. For an accurate analysis, it is necessary to segment the bone tissue from the background images, avoiding under- or overestimation of the real bone volume. Thus, segmentation methods for microCT can influence the accuracy of bone morphometry analysis. The purpose of this study was to compare two different image segmentation methods available on microCT software (subjective and objective) regarding to the human bone morphometric analysis. Sixteen samples containing a fixation screws covered by 0.5-1mm of bone were scanned using the SkyScan 1173 scanner. Three examiners segmented the microCT images subjectively and recorded the threshold values. Subsequently, an objective segmentation was also done. The 3D analysis was performed for both images using the values​ previously determined in CTAn software. Five bone morphometric parameters were calculated (BV/TV, Tb.Th, Tb.N, Tb.Sp, Conn.Den) and used as dependent variables. ANOVA showed no significant differences between the methods concerning BV/TV (p=0.424), Tb.N (p=0.672), Tb.Th (p=0.183), Tb.Sp (p=0.973) and Conn.Den (p=0.204). Intra- and interobserver agreement ranged from satisfactory to excellent (0.55-1 and 0.546-0.991, respectively). Therefore, results obtained with subjective threshorlding were similar to those obtained with objective segmentation. Since objective segmentation does not have human input and it is a truly objective method, it should be the first choice in microCT studies that concern homogeneity and high resolution human bone sample.

Full text links

We have located links that may give you full text access.
Can't access the paper?
Try logging in through your university/institutional subscription. For a smoother one-click institutional access experience, please use our mobile app.

Related Resources

For the best experience, use the Read mobile app

Mobile app image

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app

All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.

By using this service, you agree to our terms of use and privacy policy.

Your Privacy Choices Toggle icon

You can now claim free CME credits for this literature searchClaim now

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app