Robust segmentation of trabecular bone for in vivo CT imaging using anisotropic diffusion and multi-scale morphological reconstruction

Cheng Chen; Dakai Jin; Xiaoliu Zhang; Steven M. Levy; Punam K. Saha

doi:10.1117/12.2254546

13 March 2017 Robust segmentation of trabecular bone for in vivo CT imaging using anisotropic diffusion and multi-scale morphological reconstruction

Cheng Chen, Dakai Jin, Xiaoliu Zhang, Steven M. Levy, Punam K. Saha

Author Affiliations +

Proceedings Volume 10137, Medical Imaging 2017: Biomedical Applications in Molecular, Structural, and Functional Imaging; 101371T (2017) https://doi.org/10.1117/12.2254546
Event: SPIE Medical Imaging, 2017, Orlando, Florida, United States

Abstract

Osteoporosis is associated with an increased risk of low-trauma fractures. Segmentation of trabecular bone (TB) is essential to assess TB microstructure, which is a key determinant of bone strength and fracture risk. Here, we present a new method for TB segmentation for in vivo CT imaging. The method uses Hessian matrix-guided anisotropic diffusion to improve local separability of trabecular structures, followed by a new multi-scale morphological reconstruction algorithm for TB segmentation. High sensitivity (0.93), specificity (0.93), and accuracy (0.92) were observed for the new method based on regional manual thresholding on in vivo CT images. Mechanical tests have shown that TB segmentation using the new method improved the ability of derived TB spacing measure for predicting actual bone strength (R²=0.83).

Citation Download Citation

Cheng Chen, Dakai Jin, Xiaoliu Zhang, Steven M. Levy, and Punam K. Saha "Robust segmentation of trabecular bone for in vivo CT imaging using anisotropic diffusion and multi-scale morphological reconstruction", Proc. SPIE 10137, Medical Imaging 2017: Biomedical Applications in Molecular, Structural, and Functional Imaging, 101371T (13 March 2017); https://doi.org/10.1117/12.2254546

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