Trends on identification of fractured bone tissue from CT images

Keyword(s):  
2010 ◽  
Vol 44-47 ◽  
pp. 1612-1616
Author(s):  
Xiao Hui Huang ◽  
Guo Qun Zhao ◽  
Wen Guang Liu ◽  
Pei Lai Liu

The frameworks for finite element (FE) model of bone tissue available in pervious literatures, to some extent, are expert-oriented and give rise to a considerable deviation in geometric model and assignment of material property. The objective of this study is to develop a new framework to reconstruct accurate individual bone FE model based on CT images rapidly and conveniently. In image-processing, automatic segmentation of the region of interest (ROIs) improves the efficiency. The idea of enclosed volume of interest (VOI) overcomes the drawback of geometric ambiguity in Marching Cube (MC) method. Geometric model is easily obtained by a STL translator and smooth operator in home-made program. In the material property assignment, two templates for hexahedron and tetrahedron FE models, respectively, are put forth to smoothing an abrupt change of material property in the region from cortical to cancellous. K-mean algorithm is introduced to cluster material properties to improve partition performance. Finally, the new framework is demonstrated by the implementation of a femoral FE model.


2019 ◽  
Vol 34 ◽  
pp. 175-182 ◽  
Author(s):  
Mihaela Vatu ◽  
Daniela Vintilă ◽  
Dragoş Laurenţiu Popa ◽  
Veronica Mercuţ ◽  
Sanda Mihaela Popescu ◽  
...  

The human skull and the maxillary bones have a very complicated architecture, determined by the outer walls, by the internal bone structures and their joining. In this paper CAD parametric software has been used to define complex virtual models. First, the mandible and jaw were defined using CT images. These images were imported into a CAD software using specific techniques and methods. These models have been finalized in SolidWorks where the virtual model of the studied system has been generated. Then, the virtual models were exported to a software for FEA simulation and prepared for every dentistry simulations. The structure of the maxillary bones contains spongy bone tissue, cortical bone tissue along with dental tissues. Each of these tissues have certain properties (elasticity, plasticity, density) assessed by flexibility. The analysis of the mechanical tension of the dental structures has been a subject of interest in recent years in order to determine the state of tension in the dental structures and to improve the mechanical strength of these structures. Such numerical techniques can give a better understanding of reactions and interactions of individual tissues. This involves a series of computational procedures to calculate stress in each element. Field variables can be interpolated by using form functions for scientific verification and validation of clinical assumptions. Various loadings have been applied to a personalized skull obtained from CT images using CAD techniques and procedures. On this system, FEM simulations were made and maps of stress, displacements and deformations were obtained that show the mechanical behavior of the maxillary dental system. Finally, important conclusions were highlighted.


Author(s):  
Félix Paulano ◽  
Juan J. Jiménez ◽  
Rubén Pulido
Keyword(s):  

Author(s):  
R. Menaka ◽  
R. Ramesh ◽  
R. Dhanagopal

Background: Osteoporosis is a term used to represent the reduced bone density which is caused by insufficient bone tissue production to balance the old bone tissue removal. Medical Imaging procedures such as X-Ray, Dual X-Ray and Computed Tomography (CT) scans are used widely in osteoporosis diagnosis. There are several existing procedures are in practice to assist osteoporosis diagnosis which can operate using a single imaging method. Objective: The purport of this proposed work is to introduce a framework to assist the diagnosis of osteoporosis based on consenting all these X-Ray, Dual X-Ray and CT scan imaging techniques. The proposed work named as "Aggregation of Region-based and Boundary-based Knowledge biased Segmentation for Osteoporosis Detection from X-Ray, Dual X-Ray and CT images" (ARBKSOD) which is the integration of three functional modules. Methods: Fuzzy Histogram Medical Image Classifier (FHMIC), Log-Gabor Transform based ANN Training for osteoporosis detection (LGTAT) and Knowledge biased Osteoporosis Analyzer (KOA). Results: Together, all these three modules make the proposed method ARBKSOD scored the maximum accuracy of 93.11% , the highest precision value of 93.91% while processing the 6th image batch, the highest sensitivity of 92.93%., The highest specificity 93.79% is observed during the experiment by ARBKSOD while processing the 6th image batch. The best average processing time of 10244 mS is achieved by ARBKSOD while processing the 7th image batch. Conclusion: Together, all these three modules make the proposed method ARBKSOD to produce better result.


Author(s):  
Silvia Moreno ◽  
Sandra L. Caicedo ◽  
Tonny Strulovic ◽  
Juan C. Briceño ◽  
Fernando Briceño ◽  
...  

2010 ◽  
Vol 58 (S 01) ◽  
Author(s):  
W Kuroczynski ◽  
C Kampmann ◽  
R Huth ◽  
M Hartert ◽  
M Heinemann ◽  
...  
Keyword(s):  

2013 ◽  
Vol 61 (S 01) ◽  
Author(s):  
M Hamiko ◽  
M Endlich ◽  
C Krämer ◽  
C Probst ◽  
A Welz ◽  
...  
Keyword(s):  

2019 ◽  
Author(s):  
K Herdinai ◽  
S Urbán ◽  
Z Besenyi ◽  
L Pávics ◽  
N Zsótér ◽  
...  

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