Chapter title |
Finite Elements Modeling in Diagnostics of Small Closed Pneumothorax
|
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Chapter number | 150 |
Book title |
Noncommunicable Diseases
|
Published in |
Advances in experimental medicine and biology, January 2015
|
DOI | 10.1007/5584_2015_150 |
Pubmed ID | |
Book ISBNs |
978-3-31-919973-3, 978-3-31-919974-0
|
Authors |
J. Lorkowski, M. Mrzygłód, O. Grzegorowska, Lorkowski, J., Mrzygłód, M., Grzegorowska, O. |
Abstract |
Posttraumatic pneumothorax still remains to be a serious clinical problem and requires a comprehensive diagnostic and monitoring during treatment. The aim of this paper is to present a computer method of modeling of small closed pneumothorax. Radiological images of 34 patients of both sexes with small closed pneumothorax were taken into consideration. The control group consisted of X-rays of 22 patients treated because of tension pneumothorax. In every single case the model was correlated with the clinical manifestations. The procedure of computational rapid analysis (CRA) for in silico analysis of surgical intervention was introduced. It included implementation of computerize tomography images and their automatic conversion into 3D finite elements model (FEM). In order to segmentize the 3D model, an intelligent procedure of domain recognition was used. In the final step, a computer simulation project of fluid-structure interaction was built, using the ANSYS\Workbench environment of multi-physics analysis. The FEM model and computer simulation project were employed in the analysis in order to optimize surgical intervention. The model worked out well and was compatible with the clinical manifestations of pneumothorax. We conclude that the created FEM model is a promising tool for facilitation of diagnostic procedures and prognosis of treatment in the case of small closed pneumothorax. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 15 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Bachelor | 6 | 40% |
Student > Master | 2 | 13% |
Researcher | 2 | 13% |
Student > Doctoral Student | 1 | 7% |
Other | 1 | 7% |
Other | 1 | 7% |
Unknown | 2 | 13% |
Readers by discipline | Count | As % |
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Medicine and Dentistry | 11 | 73% |
Psychology | 1 | 7% |
Unknown | 3 | 20% |