• Title/Summary/Keyword: dose optimization algorithm

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IMRT optimization on multiple slice using gradient based algorithm (Gradient based algorithm을 이용한 multiple slice IMRT optimization)

  • Lee, Byung-Yong;Cho, Byung-Chul;Lee, Seok;Jung, Won-Kyun;An, Seung-Do;Choi, Eun-Kyung;Kim, Jong-Hoon;Jang, Hye-Sook
    • Progress in Medical Physics
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    • v.9 no.4
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    • pp.201-206
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    • 1998
  • IMRT optimization method on multiple slice has been developed by using gradient based algorithm. On about 10-30 CT slices including treatment region of a patient, dose optimization has been performed slice by slice to meet the condition that each organ should be exposed below maximum tolerable doses and that the tumor dose within the range of 100$\pm$5 %. Field size was limited to 8$\times$8 cm$^2$ and in this condition, beam divergence was not taken into account to calculate dose distribution. Total dose distribution was calculated by superposing each beamlet whose dose distribution had been precalculated. In order to investigate beam number dependency, dose optimization was performed for one, three, five, seven, and nine coplanar beams and then each optimization index was evaluated. It is found that optimization time was proportional to number of slices to be optimized, and the most efficient plan was obtained from the case of three-to-seven incident beams with respect to calculation time and optimization index. In conclusion, dose optimization of multiple slice was able to be obtained by repeating dose optimization of single slice under condition that the beam size is not too large to ignore beam divergence. And it turns out that result of dose optimization was so sensitive to the position of isocenter that some method to optimize isocenter position is needed to improve it.

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Multi-objective path planning for mobile robot in nuclear accident environment based on improved ant colony optimization with modified A*

  • De Zhang;Run Luo;Ye-bo Yin;Shu-liang Zou
    • Nuclear Engineering and Technology
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    • v.55 no.5
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    • pp.1838-1854
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    • 2023
  • This paper presents a hybrid algorithm to solve the multi-objective path planning (MOPP) problem for mobile robots in a static nuclear accident environment. The proposed algorithm mimics a real nuclear accident site by modeling the environment with a two-layer cost grid map based on geometric modeling and Monte Carlo calculations. The proposed algorithm consists of two steps. The first step optimizes a path by the hybridization of improved ant colony optimization algorithm-modified A* (IACO-A*) that minimizes path length, cumulative radiation dose and energy consumption. The second module is the high radiation dose rate avoidance strategy integrated with the IACO-A* algorithm, which will work when the mobile robots sense the lethal radiation dose rate, avoiding radioactive sources with high dose levels. Simulations have been performed under environments of different complexity to evaluate the efficiency of the proposed algorithm, and the results show that IACO-A* has better path quality than ACO and IACO. In addition, a study comparing the proposed IACO-A* algorithm and recent path planning (PP) methods in three scenarios has been performed. The simulation results show that the proposed IACO-A* IACO-A* algorithm is obviously superior in terms of stability and minimization the total cost of MOPP.

Analysis of Radiation Treatment Planning by Dose Calculation and Optimization Algorithm (선량계산 및 최적화 알고리즘에 따른 치료계획의 영향 분석)

  • Kim, Dae-Sup;Yoon, In-Ha;Lee, Woo-Seok;Baek, Geum-Mun
    • The Journal of Korean Society for Radiation Therapy
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    • v.24 no.2
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    • pp.137-147
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    • 2012
  • Purpose: Analyze the Effectiveness of Radiation Treatment Planning by dose calculation and optimization algorithm, apply consideration of actual treatment planning, and then suggest the best way to treatment planning protocol. Materials and Methods: The treatment planning system use Eclipse 10.0. (Varian, USA). PBC (Pencil Beam Convolution) and AAA (Anisotropic Analytical Algorithm) Apply to Dose calculation, DVO (Dose Volume Optimizer 10.0.28) used for optimized algorithm of Intensity Modulated Radiation Therapy (IMRT), PRO II (Progressive Resolution Optimizer V 8.9.17) and PRO III (Progressive Resolution Optimizer V 10.0.28) used for optimized algorithm of VAMT. A phantom for experiment virtually created at treatment planning system, $30{\times}30{\times}30$ cm sized, homogeneous density (HU: 0) and heterogeneous density that inserted air assumed material (HU: -1,000). Apply to clinical treatment planning on the basis of general treatment planning feature analyzed with Phantom planning. Results: In homogeneous density phantom, PBC and AAA show 65.2% PDD (6 MV, 10 cm) both, In heterogeneous density phantom, also show similar PDD value before meet with low density material, but they show different dose curve in air territory, PDD 10 cm showed 75%, 73% each after penetrate phantom. 3D treatment plan in same MU, AAA treatment planning shows low dose at Lung included area. 2D POP treatment plan with 15 MV of cervical vertebral region include trachea and lung area, Conformity Index (ICRU 62) is 0.95 in PBC calculation and 0.93 in AAA. DVO DVH and Dose calculation DVH are showed equal value in IMRT treatment plan. But AAA calculation shows lack of dose compared with DVO result which is satisfactory condition. Optimizing VMAT treatment plans using PRO II obtained results were satisfactory, but lower density area showed lack of dose in dose calculations. PRO III, but optimizing the dose calculation results were similar with optimized the same conditions once more. Conclusion: In this study, do not judge the rightness of the dose calculation algorithm. However, analyzing the characteristics of the dose distribution represented by each algorithm, especially, a method for the optimal treatment plan can be presented when make a treatment plan. by considering optimized algorithm factors of the IMRT or VMAT that needs to optimization make a treatment plan.

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Radiation shielding optimization design research based on bare-bones particle swarm optimization algorithm

  • Jichong Lei;Chao Yang;Huajian Zhang;Chengwei Liu;Dapeng Yan;Guanfei Xiao;Zhen He;Zhenping Chen;Tao Yu
    • Nuclear Engineering and Technology
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    • v.55 no.6
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    • pp.2215-2221
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    • 2023
  • In order to further meet the requirements of weight, volume, and dose minimization for new nuclear energy devices, the bare-bones multi-objective particle swarm optimization algorithm is used to automatically and iteratively optimize the design parameters of radiation shielding system material, thickness, and structure. The radiation shielding optimization program based on the bare-bones particle swarm optimization algorithm is developed and coupled into the reactor radiation shielding multi-objective intelligent optimization platform, and the code is verified by using the Savannah benchmark model. The material type and thickness of Savannah model were optimized by using the BBMOPSO algorithm to call the dose calculation code, the integrated optimized data showed that the weight decreased by 78.77%, the volume decreased by 23.10% and the dose rate decreased by 72.41% compared with the initial solution. The results show that the method can get the best radiation shielding solution that meets a lot of different goals. This shows that the method is both effective and feasible, and it makes up for the lack of manual optimization.

3 Dimensional IMRT Quality Assurance using the Optimization Algorithm (최적화 알고리즘을 이용한 3차원 IMRT 정도관리)

  • Shin, Dong-Ho;Park, Dong-Hyun;Kim, Joo-Young;Park, Sung-Yong;Cho, Kwan-Ho
    • Proceedings of the Korean Society of Medical Physics Conference
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    • 2004.11a
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    • pp.72-74
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    • 2004
  • To accurately verify the does of intensity modulated radiation therapy(IMRT), we developed 2 dimensional dose verification algorithm using the global optimization methode and applied to clinic. We extended to study of 3 vdimensional optimization methode, and made of arcyl 3D IMRT phantom and 3D IMRT dose verification system for film dosimetry.

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Analysis of the major factors of influence on the conditions of the Intensity Modulated Radiation Therapy planning optimization in Head and Neck (두경부 세기견조방사선치료계획 최적화 조건에서 주요 인자들의 영향 분석)

  • Kim, Dae Sup;Lee, Woo Seok;Yoon, In Ha;Back, Geum Mun
    • The Journal of Korean Society for Radiation Therapy
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    • v.26 no.1
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    • pp.11-19
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    • 2014
  • Purpose : To derive the most appropriate factors by considering the effects of the major factors when applied to the optimization algorithm, thereby aiding the effective designing of a ideal treatment plan. Materials and Methods : The eclipse treatment planning system(Eclipse 10.0, Varian, USA) was used in this study. The PBC (Pencil Beam Convolution) algorithm was used for dose calculation, and the DVO (Dose Volume Optimizer 10.0.28) Optimization algorithm was used for intensity modulated radiation therapy. The experimental group consists of patients receiving intensity modulated radiation therapy for the head and neck cancer and dose prescription to two planned target volume was 2.2 Gy and 2.0 Gy simultaneously. Treatment plan was done with inverse dose calculation methods utilizing 6 MV beam and 7 fields. The optimal algorithm parameter of the established plan was selected based on volume dose-priority(Constrain), dose fluence smooth value and the impact of the treatment plan was analyzed according to the variation of each factors. Volume dose-priority determines the reference conditions and the optimization process was carried out under the condition using same ratio, but different absolute values. We evaluated the surrounding normal organs of treatment volume according to the changing conditions of the absolute values of the volume dose-priority. Dose fluence smooth value was applied by simply changing the reference conditions (absolute value) and by changing the related volume dose-priority. The treatment plan was evaluated using Conformal Index, Paddick's Conformal Index, Homogeneity Index and the average dose of each organs. Results : When the volume dose-priority values were directly proportioned by changing the absolute values, the CI values were found to be different. However PCI was $1.299{\pm}0.006$ and HI was $1.095{\pm}0.004$ while D5%/D95% was $1.090{\pm}1.011$. The impact on the prescribed dose were similar. The average dose of parotid gland decreased to 67.4, 50.3, 51.2, 47.1 Gy when the absolute values of the volume dose-priority increased by 40,60,70,90. When the dose smooth strength from each treatment plan was increased, PCI value increased to $1.338{\pm}0.006$. Conclusion : The optimization algorithm was more influenced by the ratio of each condition than the absolute value of volume dose-priority. If the same ratio was maintained, similar treatment plan was established even if the absolute values were different. Volume dose-priority of the treatment volume should be more than 50% of the normal organ volume dose-priority in order to achieve a successful treatment plan. Dose fluence smooth value should increase or decrease proportional to the volume dose-priority. Volume dose-priority is not enough to satisfy the conditions when the absolute value are applied solely.

Optimization of Non-Local Means Algorithm in Low-Dose Computed Tomographic Image Based on Noise Level and Similarity Evaluations (노이즈 레벨 및 유사도 평가 기반 저선량 조건의 전산화 단층 검사 영상에서의 비지역적 평균 알고리즘의 최적화)

  • Ha-Seon Jeong;Ie-Jun Kim;Su-Bin Park;Suyeon Park;Yunji Oh;Woo-Seok Lee;Kang-Hyeon Seo;Youngjin Lee
    • Journal of radiological science and technology
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    • v.47 no.1
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    • pp.39-48
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    • 2024
  • In this study, we optimized the FNLM algorithm through a simulation study and applied it to a phantom scanned by low-dose CT to evaluate whether the FNLM algorithm can be used to obtain improved image quality images. We optimized the FNLM algorithm with MASH phantom and FASH phantom, which the algorithm was applied with MATLAB, increasing the smoothing factor from 0.01 to 0.05 with increments of 0.001 and measuring COV, RMSE, and PSNR values of the phantoms. For both phantom, COV and RMSE decreased, and PSNR increased as the smoothing factor increased. Based on the above results, we optimized a smoothing factor value of 0.043 for the FNLM algorithm. Then we applied the optimized FNLM algorithm to low dose lung CT and lung CT under normal conditions. In both images, the COV decreased by 55.33 times and 5.08 times respectively, and we confirmed that the quality of the image of low dose CT applying the optimized FNLM algorithm was 5.08 times better than the image of lung CT under normal conditions. In conclusion, we found that the smoothing factor of 0.043 among the factors of the FNLM algorithm showed the best results and validated the performance by reducing the noise in the low-quality CT images due to low dose with the optimized FNLM algorithm.

An intelligent optimization method for the HCSB blanket based on an improved multi-objective NSGA-III algorithm and an adaptive BP neural network

  • Wen Zhou;Guomin Sun;Shuichiro Miwa;Zihui Yang;Zhuang Li;Di Zhang;Jianye Wang
    • Nuclear Engineering and Technology
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    • v.55 no.9
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    • pp.3150-3163
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    • 2023
  • To improve the performance of blanket: maximizing the tritium breeding rate (TBR) for tritium self-sufficiency, and minimizing the Dose of backplate for radiation protection, most previous studies are based on manual corrections to adjust the blanket structure to achieve optimization design, but it is difficult to find an optimal structure and tends to be trapped by local optimizations as it involves multiphysics field design, which is also inefficient and time-consuming process. The artificial intelligence (AI) maybe is a potential method for the optimization design of the blanket. So, this paper aims to develop an intelligent optimization method based on an improved multi-objective NSGA-III algorithm and an adaptive BP neural network to solve these problems mentioned above. This method has been applied on optimizing the radial arrangement of a conceptual design of CFETR HCSB blanket. Finally, a series of optimal radial arrangements are obtained under the constraints that the temperature of each component of the blanket does not exceed the limit and the radial length remains unchanged, the efficiency of the blanket optimization design is significantly improved. This study will provide a clue and inspiration for the application of artificial intelligence technology in the optimization design of blanket.

Anisotropic Total Variation Denoising Technique for Low-Dose Cone-Beam Computed Tomography Imaging

  • Lee, Ho;Yoon, Jeongmin;Lee, Eungman
    • Progress in Medical Physics
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    • v.29 no.4
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    • pp.150-156
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    • 2018
  • This study aims to develop an improved Feldkamp-Davis-Kress (FDK) reconstruction algorithm using anisotropic total variation (ATV) minimization to enhance the image quality of low-dose cone-beam computed tomography (CBCT). The algorithm first applies a filter that integrates the Shepp-Logan filter into a cosine window function on all projections for impulse noise removal. A total variation objective function with anisotropic penalty is then minimized to enhance the difference between the real structure and noise using the steepest gradient descent optimization with adaptive step sizes. The preserving parameter to adjust the separation between the noise-free and noisy areas is determined by calculating the cumulative distribution function of the gradient magnitude of the filtered image obtained by the application of the filtering operation on each projection. With these minimized ATV projections, voxel-driven backprojection is finally performed to generate the reconstructed images. The performance of the proposed algorithm was evaluated with the catphan503 phantom dataset acquired with the use of a low-dose protocol. Qualitative and quantitative analyses showed that the proposed ATV minimization provides enhanced CBCT reconstruction images compared with those generated by the conventional FDK algorithm, with a higher contrast-to-noise ratio (CNR), lower root-mean-square-error, and higher correlation. The proposed algorithm not only leads to a potential imaging dose reduction in repeated CBCT scans via lower mA levels, but also elicits high CNR values by removing noisy corrupted areas and by avoiding the heavy penalization of striking features.

Optimization of Dose Distribution for High Dose Rate Intraluminal Therapy (고선량율 관내 방사선치료를 위한 종양선량분포의 최적화에 대한 연구)

  • Chu, Sung-Sil;Kim, Gwi-Eon;Loh, Juhn-Kyu
    • Radiation Oncology Journal
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    • v.12 no.2
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    • pp.243-252
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    • 1994
  • The use of high dose rate remote afterloading system for the treatment of intraluminal lesions necessitates the need for a more accurate of dose distributions around the high intensity brachytherapy sources, doses are often prescribed to a distance of few centimeters from the linear source, and in this range the dose distribution is very difficult to assess. Accurated and optimized dose calculation with stable numerical algorithms by PC level computer was required to treatment intraluminal lesions by high dose rate brachytherapy system. The exposure rate from sources was calculated with Sievert integral and dose rate in tissue was calculated with Meisberger equation, An algorithm for generating a treatment plan with optimized dose distribution was developed for high dose rate intraluminal radiotherapy. The treatment volume becomes the locus of the constrained target surface points that is the specified radial distance from the source dwelling positions. The treatment target volume may be alternately outlined on an x-ray film of the implant dummy sources. The routine used a linear programming formulism to compute which dwell time at each position to irradiate the constrained dose rate at the target surface points while minimizing the total volume integrated dose to the patient. The exposure rate and the dose distribution to be confirmed the result of calculation with algorithm were measured with film dosimetry, TLD and small size ion chambers.

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