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Radovic M.D.,Research and Development Center for Bioengineering Bio | Filipovic N.D.,University of Zagreb | Bosnic Z.,University of Ljubljana | Vracar P.,University of Ljubljana | Kononenko I.,University of Ljubljana
Proceedings of the IEEE/EMBS Region 8 International Conference on Information Technology Applications in Biomedicine, ITAB | Year: 2010

Arterial geometry variability is present both within and across individuals. To analyze the influence of geometric parameters on maximal wall shear stress (MWSS) in the human carotid artery bifurcation, the computer simulations were run to generate the data pertaining to this phenomenon. In our work we evaluate various prediction models for modeling relationship between geometric parameters of the carotid bifurcation and the MWSS. The results revealed the highest potential of using the neural network model for this prediction task. The achieved results and generated explanations of the prediction model represent progress in assessment of stroke risk for a given patient's geometry in real time. © 2010 IEEE.

Milankovic I.L.,University of Kragujevac | Mijailovic N.V.,University of Kragujevac | Peulic A.S.,University of Kragujevac | Nikolic D.,Research and Development Center for Bioengineering Bio | And 4 more authors.
FME Transactions | Year: 2015

The main goal of this paper is to describe two different systems that were developed for the purpose of abdominal aortic aneurysm mechanical properties investigation and to present the results of the measurements. The first system is based on the "Bubble Inflated" method and it increases the pressure of physiological saline which affects blood vessel tissue and causes mechanical deformation. The system provides recording the data about the current value of the pressure in the physiological saline by using the appropriate pressure sensor. The second system makes stretches of the vessel tissue in uni-axial direction and save the data about the force and the elongation. Both of these systems use cameras for assessment of the deformation. Obtained results from both systems are used for numerical simulation of computer model for abdominal aortic aneurysm. It gives a new avenue for application of software and hardware systems for determination of vascular tissue properties in the clinical practice. © Faculty of Mechanical Engineering, Belgrade.

Veljkovi D.,Research and Development Center for Bioengineering Bio | Filipovi N.,University of Kragujevac | Koji M.,Research and Development Center for Bioengineering Bio | Koji M.,Methodist Hospital Research Institute
Journal of Mechanics in Medicine and Biology | Year: 2012

In this work we study the effect of asymmetry and axial prestraining on the maximum effective mechanical stress in relatively small human abdominal aortic aneurysm (AAA) during a cardiac cycle. Our model is based on the fluid-structure interaction (FSI) methodology. The arterial wall is modeled using large strain and large deformation formulation, with hyperelastic material behavior, and isotropic nonlinear strain energy function (SEF) fitted to the averaged data set of biaxial tests of AAA tissue specimens. The results confirm that the magnitude of the maximum von Mises stress increases significantly with asymmetry and decreases with aneurysmal length. It is found that the amplitude in variation of the maximum effective stress changes in the same manner as the maximum stress. These results indicate that a short asymmetric AAA is under significant dynamic stress, which might be one of the important factors in a progressive AAA growth over time. It is also found that, in most considered cases, magnitude and amplitude of the maximum effective stress of an AAA is smaller when the artery is pre-stretched in axial direction, while a pre-stretched artery with aneurysm has slightly larger relative volume change of lumen during cardiac cycle than the unstretched AAA. © 2012 World Scientific Publishing Company.

Bosnic Z.,University of Ljubljana | Vracar P.,University of Ljubljana | Radovi M.D.,Research and Development Center for Bioengineering Bio | Devedzic G.,University of Zagreb | And 2 more authors.
IEEE Transactions on Information Technology in Biomedicine | Year: 2012

One of the most common causes of human death is stroke, which can be caused by carotid bifurcation stenosis. In our work, we aim at proposing a prototype of a medical expert system that could significantly aid medical experts to detect hemodynamic abnormalities (increased artery wall shear stress). Based on the acquired simulated data, we apply several methodologies for1) predicting magnitudes and locations of maximum wall shear stress in the artery, 2) estimating reliability of computed predictions, and 3) providing user-friendly explanation of the models decision. The obtained results indicate that the evaluated methodologies can provide a useful tool for the given problem domain. © 2012 IEEE.

Radovic M.,Research and Development Center for Bioengineering Bio | Djokovic M.,University of Kragujevac | Peulic A.,University of Kragujevac | Filipovic N.,Research and Development Center for Bioengineering Bio | Filipovic N.,University of Zagreb
13th IEEE International Conference on BioInformatics and BioEngineering, IEEE BIBE 2013 | Year: 2013

One of the leading causes of cancer death among women is breast cancer. In our work we aim at proposing a prototype of a medical expert system (based on data mining techniques) that could significantly aid medical experts to detect breast cancer. This paper presents the CAD (computer aided diagnosis) system for the detection of normal and abnormal pattern in the breast. The proposed system consists of four major steps: the image preprocessing, the feature extraction, the feature selection and the classification process that classifies mammogram into normal (without tumor) and abnormal (with tumor) pattern. After removing noise from mammogram using the Discrete Wavelet Transformation (DWT), first is selected the region of interest (ROI). By identifying the boundary of the breast, it is possible to remove any artifact present outside the breast area, such as patient markings. Then, a total of 20 GLCM features are extracted from the ROI, which were used as inputs for classification algorithms. In order to compare the classification results, we used seven different classifiers. Normal breast images and breast image with masses (total 322 images) used as input images in this study are taken from the mini-MIAS database. © 2013 IEEE.

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