P. Somogyi

24759511800

Publications - 7

Modeling the Correlation of Human Vertebral Body Volumes

Balázs Benyó P. Somogyi Bálint Szabó K. Kovács Sándor Bazsó Á Szlávecz Árpád Viola

Publication Name: IFAC Papersonline

Publication Date: 2023-07-01

Volume: 56

Issue: 2

Page Range: 9030-9035

Description:

Anatomical parameters of the human body strongly correlate with each other. Modelling these dependencies enables the creation of a realistic anatomical human body model that can be parameterized. Such a model can be used for several diagnostic processes to identify abnormalities or even give guidance in surgical interventions. This paper proposes a probabilistic model describing the dependencies between the vertebral body volumes of humans from the Caucasian human race. As demonstrated, the proposed model can accurately describe the relationship between the vertebral body volumes and is used for the prediction of an unknown vertebral volume based on a known one. The probabilistic model is created by using the CT segmentation of 37 patients.

Open Access: Yes

DOI: 10.1016/j.ifacol.2023.10.133

Finite Element Simulation Based Analysis of Valve-sparing Aortic Root Surgery

Tamás Umenhoffer Balázs Benyó P. Somogyi K. Kovács Róbert Nagy Bernhard Laufer Anikó Kubovje Á Szlávecz Tamás Szerafin

Publication Name: IFAC Papersonline

Publication Date: 2020-01-01

Volume: 53

Issue: 2

Page Range: 16037-16042

Description:

The valve-sparing aortic root surgery is frequently used in the treatment of aortic root enlargement or aortic root aneurysm. The currently used common surgical practice assumes that the valve leaflets are distributed evenly around the circle defined by the aorta wall which is frequently a false assumption according to hart anatomy studies. A finite element simulation based method is proposed in this study for the analysis of the alternative surgical outcomes of the valve-sparing aortic root surgery. The simulation methods allow the definition of the aortic valve leaflet commissure positions and the diameter of the graft used to replace the aortic root. The suggested methods are able to estimate and quantitatively compare the hemodynamic functions and the robustness of the aortic valve functions. The corresponding modeling environment makes possible the easy definition of the patient specific aortic root model that is used as an input of the simulation. The initial validation of the simulation method was done by a real patient data based simulation study. These results suggest that the currently used surgical practice can be improved.

Open Access: Yes

DOI: 10.1016/j.ifacol.2020.12.409

Initial value selection of the model parameters in the curve fitting phase of the dynamic SPECT imaging

Balázs Benyó P. Somogyi G. Hesz K. Kovács Zsófia Barna Á Szlávecz

Publication Name: IFAC Papersonline

Publication Date: 2018-01-01

Volume: 51

Issue: 27

Page Range: 241-246

Description:

The dynamic SPECT (Single Photon Emission Computed Tomography) reconstruction algorithm developed in our prior work reconstructs the parameters of the time activity curve for each image voxel directly from the projection images. In each iterations of the SPECT reconstruction beyond the static 3D MLEM (Maximum Likelihood Expectation Maximization) step, the algorithm performs a fitting process for each voxel in order to estimate the parameters describing the function of the examined organ considering that the time frames are not independent from each other. In real cases the fitted curve is nonlinear function of these parameters, it is usually described as the sum of exponential functions. In order to estimate the parameters properly, an iterative root-finding method is applied. In the current study the Newton-Raphson method is used. The selection of a proper initial value for the root-finding method is critical in order to achieve convergence of the fitting process. If the initial guess is not appropriate, the root-finding algorithm can diverge or converge to an inappropriate parameter set that can result in unacceptable reconstructed parameters. This affects then the subsequent MLEM iterations, also neighboring voxels and breaks the reconstruction. In this work we investigated different methods to calculate the initial values of the fitting process and evaluated the reconstructed parameter set of the dynamic SPECT reconstruction algorithm. Three different methods are investigated, one that uses the fitted parameters of the previous MLEM iteration, one that is based on the sum of the geometrical series of the exponentials and one that calculates the best guess using both methods. The three methods were compared by benchmark reconstruction cases using a mathematical phantom. In each reconstruction different initial value selection method was applied then the time activity curves of the voxels belonging to the same tissue were statistically evaluated using the reconstructed parameters. In the study no significant differences were found in the mean value of the reconstructed parameters. The standard deviation of the parameters was similar between the two simple approaches, however, the combination of the methods resulted in better statistical performance.

Open Access: Yes

DOI: 10.1016/j.ifacol.2018.11.635

Classification of Time Series Using Singular Values and Wavelet Subband Analysis with ANN and SVM Classifiers

Balázs Benyó P. Somogyi B. Paláncz

Publication Name: Journal of Advanced Computational Intelligence and Intelligent Informatics

Publication Date: 2006-07-01

Volume: 10

Issue: 4

Page Range: 498-503

Description:

Oscillation of cerebral blood flow (CBF) in physiological or pathophysiological brain states is common, therefore it is promising to identify cerebral circulation disorders based on CBF signal classification. To characterize temporal blood flow patterns, we applied two feature extractions, spectral matrix and wavelet subband analysis. To distinguish between different physiological states, two different classifications have been developed – the radial basis function-based neural network and a support vector classifier with a Gaussian kernel. Feature extraction and classification are evaluated and their efficiency compared. Calculation was done using Mathematica 5.1 and its Wavelet Application.

Open Access: Yes

DOI: 10.20965/jaciii.2006.p0498

Classification of time series using singular values and wavelet subband analysis with ANN and SVM classifiers

Balázs Benyó P. Somogyi Péter Várady B. Paláncz

Publication Name: Ines 05 IEEE 9th International Conference on Intelligent Engineering Systems Proceedings

Publication Date: 2005-01-01

Volume: 2005

Issue: Unknown

Page Range: 239-243

Description:

Oscillation of the cerebral blood flow (CBF) is a common feature in several physiological or pathophysiological states of the brain. It is promising to identify the disorders of the cerebral circulation based on the classification of CBF signals. In order to distinguish between different physiological states, two different classification methods have been developed; a Radial Basis Function based Neural Network and a Support Vector Classifier with Gaussian kernel. In order to describe the temporal blood flow patterns, two feature extraction procedures were applied; spectral matrix and wavelet subband analysis. These feature extraction and classification methods are evaluated and their efficiencies are compared. The computations were carried out with Mathematica 5.1 and its Wavelet Application. © 2005 IEEE.

Open Access: Yes

DOI: 10.1109/INES.2005.1555165

Characterization of cerebral blood flow oscillations using different classification methods

Balázs Benyó P. Somogyi Zoltán Benyó B. Paláncz

Publication Name: IFAC Proceedings Volumes IFAC Papersonline

Publication Date: 2005-01-01

Volume: 16

Issue: Unknown

Page Range: 214-219

Description:

Oscillation of the cerebral blood flow (CBF) is a common feature in several physiological or pathophysiological states of the brain. It is a promising opportunity to identify the disorders of the cerebral circulation based on the classification of CBF signals. Three classification models are developed with different heuristic in order to carry out the systematic classification based on a problem specific feature extraction. The efficiency of the selected classification methods are evaluated and compared. Copyright © 2005 IFAC.

Open Access: Yes

DOI: 10.3182/20050703-6-cz-1902.02150

Biomedical Engineering Education and Related Research Activity in Hungary

Balázs Benyó P. Somogyi L. Kovács L. Szilágyi Zoltán Benyó Péter Várady

Publication Name: Annual International Conference of the IEEE Engineering in Medicine and Biology Proceedings

Publication Date: 2003-12-01

Volume: 4

Issue: Unknown

Page Range: 3533-3535

Description:

Biomedical Engineering is a relatively new interdisciplinary science. This paper presents the biomedical engineering activity, which is carried out at Budapest University of Technology and Economics and its partner institutes. In the first part the main goals and the curriculum of the Biomedical Engineering ducation Program (BMEEP) is presented. The second part of the paper summarizes the most important biomedical engineering researches carried out mostly in the Biomedical Engineering Laboratory of our university.

Open Access: Yes

DOI: DOI not available