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The analysis of porous structures in bio-ceramics is crucial for understanding their suitability for biomedical applications, particularly in bone regeneration and repair. Traditional methods for pore analysis, while useful, often fall short in accurately delineating individual pores and quantifying their characteristics due to limitations in resolving connected pores and imprecise volume measurements. This work proposes a novel adaptive method based on morphological operation algorithms to address these challenges, enabling precise calculation of porosity and its classification.
The objective of our work is to carry out a qualitative and quantitative evaluation of the porous microstructure of HAP bio-ceramic using SEM and µCT images.
An accurate method is proposed to characterize pores and separate them at the same time. The method makes it possible to easily calculate many quantitative measurements, in particular those that provide information on the connection and the size distribution of the pores.
To realize those tasks, an adaptive method based on the morphological operation algorithm is proposed.
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The conventional method of openings alone is not sufficient to achieve our objective. It presents incorrect separations of the pores, imprecise volumes of each pore and therefore a limitation of calculations. The proposed method lets us to calculate precisely a specific porosity and define classes of porosity.
To separate the pores structure from the rest of sample, we carefully choose the threshold. It converts a gray-scale image into a binary image where the two levels are assigned to pixels that are below or above the specified threshold value. It is useful to be able to separate out the regions of the image corresponding to pores which interests us from the rest of sample.
However, the simple threshold does not allow separating pores between them depending on their size.
Mathematical Morphology has been broadly used in image processing and shape analysis of features of interest. The fundamental morphological set operations consist of union, intersection and complement. The operands of the set operations are the original data and data translated from the original with a reference shape called a structuring element. A structuring element can be formed by a set of vectors. Then the fundamental mathematical morphological operations called dilation and erosion can be defined with the basic Minkowski set operations called addition and subtraction.
Erosion of an image I by the structure element H is given by the set operation
I H = {p ∈ Z2 | (p + q) ∈ I, for every q ∈ H} = ∩I-q. (2)
Dilation of an image I by the structure element H is given by the set operation
I ⊕ H = {(p + q)| p ∈ I, q ∈ H} = ⋃Hp =⋃Iq. (3)
Holes in the foreground that are smaller than H will be filled.
Erosion reduces the size of the pores by eroding its outline and dilation by dilating its outline, with the predefined structure element. Erosion followed by dilation is called opening. [34] They are mathematical morphology tools that process images based usually on shapes and most commonly change them. Those operations affect directly the efficiency of pores measurements especially those with irregular shape. For an efficient porosity study, it is useful to separate the pores from one another and label them. This allows us to calculate many parameters mainly the volume, the apparent perimeter and the surface contact.
Moreover, the conventional method based on openings alone is inappropriate for an efficient quantitative analysis. This approach does not take into account convexity hypotheses on the forms encountered and does not divide them to achieve a distribution of the separated pores.
To surpass those limits, a method based on the use of morphological operations is proposed. Successive openings operation are computed with structuring element increasing in diameter to make the particles disappear progressively. The difference between the images before and after an opening, corresponds to the total volume of the particles disappeared. The volume and the contact area of the isolated elements are calculated with the original element. This calculation is done via a voxel/pixel path in the subtracted image. Neighbouring voxels/pixels of components are compared; a voxel/pixel having different gray level value neighbours in the original image is indeed a contact surface.
A component may be connected with more than one other component. The method allows us to calculate for each component, the number of contacts (Nsc) with other interfaces. After those operations, the small elements and the corners belonging to the pore, which are found in the reference image, disappear. The conventional method considers them as distinct components, but the originality of our method is that it does not take them into account on the basis of a geometric criterion. The contact surface, the number of contact surfaces with the other elements, and the total and specific pore volume will be calculated.
Since the structuring element of the conventional method moves across the image, some intricate images may not be properly processed. Consequently, an artefact in the shape of structural elements may be generated at the object periphery or squarely the periphery shape changes that leads also directly to a bad quantitative study. To overcome this, the analyses are carried out on the contact surface; if it is larger than the surface area of the subtracted element, the element is left with its original structure otherwise, it is not taken into account in the calculation of the porosity. We then solve the problem of small connected structures considered as a single pore which disappears after the opening. Fig. 5 illustrates the flowchart of the proposed method to calculate porosity parameters.
This work presents a significant advancement in the characterization of the porous microstructure of HAP bio-ceramics, employing a sophisticated method based on morphological operations. The proposed method not only provides accurate quantitative measurements of porosity but also offers a deeper insight into the microstructural properties critical for biomedical applications. This approach paves the way for the development of bio-ceramics with tailored porosity characteristics, optimizing their performance in bone regeneration and repair.
Optimizing Porosity Measurement in HAP Bio-Ceramics Using Morphological Image Analysis. (2024, Feb 22). Retrieved from https://studymoose.com/document/optimizing-porosity-measurement-in-hap-bio-ceramics-using-morphological-image-analysis
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