Automatic Processing and Analysis of the Quality Healing of Derma Injury

Семенова, Е. В.; Gerasimov, Oleg V.; Koroleva, E. V.; Ahmetov, Nafis; Baltina, Tatyana; Sachenkov, Oskar

doi:10.1007/978-3-319-97286-2_10

Cited by 6 publications

(7 citation statements)

References 15 publications

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“…Sections were stained with hematoxylin-eosin. The histology of bone tissue was analyzed [25,26]. All experiments were performed according to bioethical standards and were approved by the local ethical committee of the Kazan Federal University (Protocol meeting No.2 of May 5, 2015).…”

Section: Methodsmentioning

confidence: 99%

Design and Optimization Lattice Endoprosthesis for Long Bones: Manufacturing and Clinical Experiment

Bolshakov

Raginov

Egorov³

et al. 2020

Materials

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The article is devoted to the construction of lattice endoprosthesis for a long bone. Clinically, the main idea is to design a construction with the ability to improve bone growth. The article presents the algorithm for such a design. The construction should be produced by additive manufacturing. Such an approach allows using not only metallic materials but also ceramics and polymers. The algorithm is based on the influence function as a method to describe the elementary cell geometry. The elementary cell can be described by a number of parameters. The influence function maps the parameters to local stress in construction. Changing the parameters influences the stress distribution in the endoprosthesis. In the paper, a bipyramid was used as an elementary cell. Numerical studies were performed using the finite element method. As a result, manufacturing construction is described. Some problems for different orientations of growth are given. The clinical test was done and histological results were presented.

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Section: Methodsmentioning

confidence: 99%

Design and Optimization Lattice Endoprosthesis for Long Bones: Manufacturing and Clinical Experiment

Bolshakov

Raginov

Egorov³

et al. 2020

Materials

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“…In this case, the fabric tensor can be calculated as the square root of the inverse approximation matrix. Usually the quadratic form [19,27,29] is used to approximate the MIL:…”

Section: Methodsmentioning

confidence: 99%

“…Previous technique [29] for MIL approximation was generalized for three-dimensional space. The MIL data in a material can be represented as a vector:…”

Section: Methodsmentioning

confidence: 99%

Automatic processing and analysis of the structural properties of bone tissue

et al. 2020

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The volumetric distribution of bone tissue can be analysed in terms of orthotropic medium. In this case, it is important to define the orthotropic directions. Nowadays, computed tomography methods allow getting such information. The method for automation such analysis is presented. Firstly, the threshold of binarization should be calculated. Then the sample should be meshed and each element should be binarized. After that fabric tensor, eigenvalues, eigenvectors and fractional anisotropy can be calculated for each element. Statistical methods were used to analyse the field of the obtained data. Described methods were used on a bone sample. It was shown that for a sample the fabric tensor is constant and the fractional anisotropy is close to zero. That’s means that the medium in the sample was isotropic.

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“…To calculate the degree of anisotropy, a fabric tensor was used [23][24][25][26]. For this purpose, all data should meshed by 2-D Cartesian grid and fabric tensor should be calculated for every element.…”

Section: Macro Scale Datamentioning

confidence: 99%

“…where ϕ, r -polar coordinate of i-th element's center, an investigated parameter can be a degree of anisotropy η in the ith element, h -1st or 2nd eigenvector (analogically in the i-th element). The algorithm calculation the fabric tensor distribution can be described as: The description of the algorithm presented in detail in Semenova et al [23] with an example for estimation the quality of collagen recovery using microscopy data. For the data, the correlation matrix was calculated and singular value decomposition was used.…”

Section: Macro Scale Datamentioning

confidence: 99%

Automation of Bone Tissue Histology

et al. 2019

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In abstract methods of automation of histology, bone structure is considered. Possible inputs are snapshots from a microscope or computed tomography slices. An algorithm is proposed that differentiates objects according to their color (or grayscale) and recover morphology topology. An algorithm to separate morphological objects by their dimensions and color parameters was built. Measured parameters were bone surface, bone area, porosity, cortical thickness, canal number, canal area, and etc. Additionally, we measured the anisotropy properties of the bone tissue: distribution of porosity direction and degree of porosity elongation. A bone example was scanned by computed tomography. All data were measured by the proposed method and the results presented. An example algorithm of work on computed tomography data is shown in this work.

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Automatic Processing and Analysis of the Quality Healing of Derma Injury

Cited by 6 publications

References 15 publications

Design and Optimization Lattice Endoprosthesis for Long Bones: Manufacturing and Clinical Experiment

Design and Optimization Lattice Endoprosthesis for Long Bones: Manufacturing and Clinical Experiment

Automatic processing and analysis of the structural properties of bone tissue

Automation of Bone Tissue Histology

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