Determination of bone porosity based on histograms of 3D μCT images

M Cieszko,P Gadzała,Z Szczepański

doi:10.1007/s10853-014-8654-9

M Cieszko, P Gadzała + Show 1 more

Open Access

https://doi.org/10.1007/s10853-014-8654-9

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Abstract

A new method is proposed for direct determination of bone porosity based on histograms of 3D µCT scans and for precise definition of the global image segmentation threshold, preserving assessed porosity in the reconstructed binary image of the bone sample. In this method, the normed histogram is considered to be a probability distribution of voxel density (CT number or gray level) in the scan. It is a linear combination of two distributions characterizing the frequency of occurrence of voxels of pore and matrix type with various densities. Volume porosity, in this model, defines the probability of pore voxel occurrence in the whole set of voxels in the scan of the sample. This parameter and the parameters of both probability distributions are determined by an optimization method. The new method was used to determine the porosity and segmentation thresholds for µCT images of two 3D samples of human cancellous bone. The results were compared with those determined by the standard method and Otsu’s method. The new method allows the porosity and the image segmentation threshold to be determined even in cases where use of the other methods is questionable or impossible.

Highlights

Identification of the microscopic geometry of bone tissue and macroscopic parameters of its pore space structure is a very important issue in the study of the physical propertiesThere are many methods for identifying the microscopic pore geometry of porous materials and their macroscopic parameters, such as optical microscopy, ultrasonic microscopy and porosimetry, mercury porosimetry, electric spectroscopy, permeametry, and gas pycnometry
A new method is proposed for direct determination of bone porosity based on histograms of 3D lCT scans and for precise definition of the global image segmentation threshold, preserving assessed porosity in the reconstructed binary image of the bone sample
The set of voxels in the scan sample form the overall population of the analyzed voxels, and their density is a random variable, the probability distribution function of which, denoted by w(q), we identify with the normalized histogram of the sample of porous material’s scan

Summary

Introduction

Identification of the microscopic geometry of bone tissue and macroscopic parameters of its pore space structure is a very important issue in the study of the physical propertiesThere are many methods for identifying the microscopic pore geometry of porous materials and their macroscopic parameters, such as optical microscopy, ultrasonic microscopy and porosimetry, mercury porosimetry, electric spectroscopy, permeametry, and gas pycnometry. Microcomputed tomography (lCT) [1,2,3] is another of these methods It is a very modern, nondestructive method used in various branches of science and engineering [4,5,6,7] for identification of the spatial structure of heterogeneous materials and small physical objects. Microtomographic images of samples of porous materials form a basis for the reconstruction of the microscopic pore space geometry or matrix architecture This allows identification of the stochastic characteristics, microscopic and macroscopic parameters of the pore space and matrix structure, material constants, and their directional characteristics [8,9,10,11,12,13,14,15,16,17,18]. Pure geometrical methods [9, 14, 19,20,21] and methods of simulation of physical processes at microscopic level [12, 13, 16, 18] are used

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