• Radiation Oncology Journal
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• v.28 no.4
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• pp.238-248
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• 2010

Purpose: To compare the dose distributions between three-dimensional (3D) and four-dimensional (4D) radiation treatment plans calculated by Ray-tracing or the Monte Carlo algorithm, and to highlight the difference of dose calculation between two algorithms for lung heterogeneity correction in lung cancers. Materials and Methods: Prospectively gated 4D CTs in seven patients were obtained with a Brilliance CT64-Channel scanner along with a respiratory bellows gating device. After 4D treatment planning with the Ray Tracing algorithm in Multiplan 3.5.1, a CyberKnife stereotactic radiotherapy planning system, 3D Ray Tracing, 3D and 4D Monte Carlo dose calculations were performed under the same beam conditions (same number, directions, monitor units of beams). The 3D plan was performed in a primary CT image setting corresponding to middle phase expiration (50%). Relative dose coverage, D95 of gross tumor volume and planning target volume, maximum doses of tumor, and the spinal cord were compared for each plan, taking into consideration the tumor location. Results: According to the Monte Carlo calculations, mean tumor volume coverage of the 4D plans was 4.4% higher than the 3D plans when tumors were located in the lower lobes of the lung, but were 4.6% lower when tumors were located in the upper lobes of the lung. Similarly, the D95 of 4D plans was 4.8% higher than 3D plans when tumors were located in the lower lobes of lung, but was 1.7% lower when tumors were located in the upper lobes of lung. This tendency was also observed at the maximum dose of the spinal cord. Lastly, a 30% reduction in the PTV volume coverage was observed for the Monte Carlo calculation compared with the Ray-tracing calculation. Conclusion: 3D and 4D robotic radiotherapy treatment plans for lung cancers were compared according to a dosimetric viewpoint for a tumor and the spinal cord. The difference of tumor dose distributions between 3D and 4D treatment plans was only significant when large tumor movement and deformation was suspected. Therefore, 4D treatment planning is only necessary for large tumor motion and deformation. However, a Monte Carlo calculation is always necessary, independent of tumor motion in the lung.

• Journal of Biomedical Engineering Research
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• v.25 no.2
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• pp.89-95
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• 2004

Intensity-modulated radiation therapy (IMRT) often uses small beam segments. The heterogeneity effect is well known for relatively large field sizes used in the conventional radiation treatments. However, this effect is not known in small fields such as the beamlets used in IMRT. There are many factors that can cause errors in the small field i.e. electronic disequilibrium and multiple electron scattering. This study prepared geometrically regular heterogeneous phantoms, and compared the measurements with the calculations using the Convolution/Superposition algorithm and Monte Carlo method for small beams. This study used the BEAM00/EGS4 code to simulate the head of a Varian 2300C/D. The commissioning of a 6MV photon beam were performed from two points of view, the beam profiles and depth doses. The calculated voxel size was 1${\times}$1${\times}$2$\textrm{cm}^2$ with field sizes of 1${\times}$1$\textrm{cm}^2$, 2${\times}$2$\textrm{cm}^2$, and 5${\times}$5$\textrm{cm}^2$. The XiOTM TPS (Treatment Planning System) was used for the calculation using the Convolution/Superposition algorithm. The 6MV photon beam was irradiated to homogeneous (water equivalent) and heterogeneous phantoms (water equivalent ＋ air cavity, water equivalent ＋ bone equivalent). The beam profiles were well matched within :t1 mm and the depth doses were within ${\pm}$2%. In conclusion, the dose calculations of the Convolution/Superposition and Monte Carlo simulations showed good agreement with the film measurements in the small field.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.5
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• pp.812-817
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• 2011

In this paper, we propose new data association method called the Highest Probability Data Association with Limited Measurement Numbers(HPDA-LIMN) using a Signal Itensity Ordering method applied to tracking in clutter environment. The performance of HPDA-LIMN algorithm is tested in a series of Monte Carlo simulations runs and is compared with the exiting data association method in cluttered environment.

• Journal of the Korean Statistical Society
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• v.23 no.1
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• pp.63-78
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• 1994

For discrimination with binary variables, reformulated full and first order Bahadur model with incomplete observations are presented. This allows prior probabilities associated with multiple population to be estimated for the sample-based classification rule. The EM algorithm is adopted to provided the maximum likelihood estimates of the parameters of interest. Some experiences with the models are evaluated and discussed.

• Journal of applied mathematics & informatics
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• v.3 no.2
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• pp.253-264
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• 1996

The generalized logit model of nominal type with random regressors is studied for bootstrapping. We assess the accuracy of some estimators for our generalized logit model using a Monte Carlo simu-lation. That is we study the finite sample properties containing the consistency and asymptotic normality of the maximum likelihood es-timators. Also we compare Newton Raphson algorithm with BHHH algorithm.

• Journal of the Korean Institute of Navigation
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• v.16 no.3
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• pp.65-76
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• 1992

An algorithm to determine the optimum nominal value of geometrical and material parameters in divice modelling is proposed. The algorithm uses the yield and variance prediction formula and Monte-Carlo analysis. The performance specification of the noise figure must also be satisfied. In this paper, the total number of considered devices is 1000, and each parameter of geometrical and material parameters is generated randomly within the limits of ${\pm}3%$ of nominal value, and the distribution of 1000 geometrical and material parameters is gaussing distribution.

• Communications for Statistical Applications and Methods
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• v.8 no.1
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• pp.109-115
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• 2001

Wavelet coefficients are known to have decorrelating properties, since wavelet is orthonormal transformation. but empirically, those wavelet coefficients of images, like edges, are not statistically independent. Jansen and Bultheel(1999) developed the empirical Bayes approach to improve the classical threshold algorithm using local characterization in Markov random field. They consider the clustering of significant wavelet coefficients with uniform distribution. In this paper, we developed wavelet thresholding algorithm using Laplacian distribution which is more realistic model.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10b
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• pp.676-678
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• 1998

본 논문에서는 Information-Based Complexity분양의 문제들 중 그 complexity를 계산하기 매우 어렵거나 불가능한 문제들의 오차를 분석하기 위해서 k-fold Wiener process를 생성하는 algorithm에 대해 연구하고, 이 algorithm을 실제 프로그램 하였다. 또한 이 프로그램이 생성한 함수가 실제 k-fold Wiener process와 아주 근사하다는 것을 Kolmogorov-Smirnov test를 통하여 보여준다. 이 프로그램을 이용하면 여러 문제들의 average case error를 Monte-Carlo Simulation 과 같은 방법을 사용하여 실험적으로 계산할 수 있다.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.32 no.10
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• pp.360-366
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• 1983

In this paper, operation cost of the system is calculated by the probabilistic simulation method. And it is proved that only 20 iterative simulations are enough to get the result obtain by the Monte Carlo simulation method which requires more than 1000 iterative simulations. In the probabilistic simulation method we use the ranking of line contingency which is derived from the line countingency selection algorithm proposed in (2). In using this method the nature of the sparsity of the power system is used.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.1935-1937
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• 2001

In this paper, the position determination problem for geometry PIG is considered. The PIG system is a device to examine the gas pipeline condition and detect the accurate position of dent or any undesirable state. In order to determine the position, the smoothing algorithm has been used and its performance anyalsis has been done by Monte Carlo simulation technigue.