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On-line Access: 2020-02-04

Received: 2019-12-02

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Bio-Design and Manufacturing  2020 Vol.3 No.1 P.71-82


Computer‑aided CT image processing and modeling method for tibia microstructure

Author(s):  Pengju Wang, Su Wang

Affiliation(s):  School of Mechanical Engineering, Harbin Institute of Technology, Harbin, China; more

Corresponding email(s):   wangpengju188@163.com

Key Words:  Tibia, CT image processing, Fractal dimension, Support vector machine, 3D modeling

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Pengju Wang, Su Wang. Computer‑aided CT image processing and modeling method for tibia microstructure[J]. Journal of Zhejiang University Science D, 2020, 3(1): 71-82.

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author="Pengju Wang, Su Wang",
journal="Journal of Zhejiang University Science D",
publisher="Zhejiang University Press & Springer",

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%T Computer‑aided CT image processing and modeling method for tibia microstructure
%A Pengju Wang
%A Su Wang
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%DOI 10.1007/s42242-020-00063-x

T1 - Computer‑aided CT image processing and modeling method for tibia microstructure
A1 - Pengju Wang
A1 - Su Wang
J0 - Journal of Zhejiang University Science D
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EP - 82
%@ 1869-1951
Y1 - 2020
PB - Zhejiang University Press & Springer
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DOI - 10.1007/s42242-020-00063-x

We present a method for computed tomography (CT) image processing and modeling for tibia microstructure, achieved by using computer graphics and fractal theory. Given the large-scale image data of tibia species with DICOM standard for clinical applications, we take advantage of algorithms such as image binarization, hot pixel removing and close operation to obtain visually clear image for tibia microstructure. All of these images are based on 20 CT scanning images with 30 μm slice thickness and 30 μm interval and continuous changes in pores. For each pore, we determine its profle by using an improved algorithm for edge detection. Then, to calculate its three-dimensional fractal dimension, we measure the circumference perimeter and area of the pores of bone microstructure using a line ftting method based on the least squares. Subsequently, we put forward an algorithm for the pore profles through ellipse ftting. The results show that the pores have signifcant fractal characteristics because of the good linear correlation between the perimeter and the area parameters in log–log scale coordinates system, and the ratio of the elliptical short axis to the long axis through ellipse ftting tends to 0.6501. Based on support vector machine and structural risk minimization principle, we put forward a mapping database theory of structure parameters among the pores of CT images and fractal dimension, Poisson’s ratios, porosity and equivalent aperture. On this basis, we put forward a new concept for 3D modeling called precision-measuring digital expressing to reconstruct tibia microstructure for human hard tissue.

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