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Artículos de revistas sobre el tema "Dose Computation"

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Publicado: 25 de enero de 2025
Última modificación: 31 de julio de 2025

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1

Knöös, T. "3D dose computation algorithms." Journal of Physics: Conference Series 847 (May 2017): 012037. http://dx.doi.org/10.1088/1742-6596/847/1/012037.

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2

Battista, J., J. Chen, S. Sawchuk, and G. Hajdok. "Evolution of 3D X-Ray Dose Computation Algorithms." Journal of Physics: Conference Series 2630, no. 1 (2023): 012008. http://dx.doi.org/10.1088/1742-6596/2630/1/012008.

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Abstract Radiation treatment planning of individual cancer patients relies on the accurate computation of dose distributions in irradiated tissue. Inaccurate dose maps have the potential to mislead clinical decision-making and compromise the balance between effective tumour control and side effects in surrounding normal tissue. In the context of this conference, 3D dosimetry is important for the experimental validation of computed dose distributions. Dose computation methods for external beams of high energy x rays have evolved over the past decade with computer simulation models more closely
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3

Cutanda Henríquez, Francisco, and Silvia Vargas Castrillón. "Confidence intervals in dose volume histogram computation." Medical Physics 37, no. 4 (2010): 1545–53. http://dx.doi.org/10.1118/1.3355888.

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4

Laub, W., M. Alber, M. Birkner, and F. Nüsslin. "Monte Carlo dose computation for IMRT optimization*." Physics in Medicine and Biology 45, no. 7 (2000): 1741–54. http://dx.doi.org/10.1088/0031-9155/45/7/303.

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5

Tang, Man-Lai, Karim F. Hirji, and Stein E. Vollset. "Exact power computation for dose—response studies." Statistics in Medicine 14, no. 20 (1995): 2261–72. http://dx.doi.org/10.1002/sim.4780142009.

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6

Sandison, G. A., and L. S. Papiez. "Dose computation applications of the electron loss model." Physics in Medicine and Biology 35, no. 7 (1990): 979–97. http://dx.doi.org/10.1088/0031-9155/35/7/013.

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7

Mohan, R., C. Chui, and L. Lidofsky. "Differential pencil beam dose computation model for photons." Medical Physics 13, no. 1 (1986): 64–73. http://dx.doi.org/10.1118/1.595924.

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8

Siebert, Frank-André, Ping Jiang, Rene Baumann, et al. "Dose Computation of Keloids in Brachytherapy: Tg-43 or Model-Based-Dose-Calculation?" Brachytherapy 15 (May 2016): S149. http://dx.doi.org/10.1016/j.brachy.2016.04.262.

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9

Dray, Nicolas, Nicolas Mary, Cédric Dossat, Jefferson Bourgoin, and Nathalie Chatry. "An overview of last decade’s developments in RayXpert®, a 3D Monte Carlo code." EPJ Nuclear Sciences & Technologies 10 (2024): 10. http://dx.doi.org/10.1051/epjn/2024013.

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This article provides an overview of the developments made over the last 10 years within RayXpert®, a CAD-based geometry 3D Monte Carlo software developed by TRAD – Tests & Radiations. The main features of RayXpert® are its 3D Monte Carlo engine and its CAD-based geometry. It is also possible to import STEP file, automatically detect overlaps, and perform parallel Monte Carlo computations. During the last 10 years, numerous new features were added to the software: TTB approximation, dose and flux mapping, computation resumption, radioactive decay computation, script support, MPI computatio
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10

Panitsa, E., J. C. Rosenwald, and C. Kappas. "Developing a dose-volume histogram computation program for brachytherapy." Physics in Medicine and Biology 43, no. 8 (1998): 2109–21. http://dx.doi.org/10.1088/0031-9155/43/8/009.

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11

Wu, Xingen, and Yunping Zhu. "A neural network regression model for relative dose computation." Physics in Medicine and Biology 45, no. 4 (2000): 913–22. http://dx.doi.org/10.1088/0031-9155/45/4/307.

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12

Mohan, R., I. Y. Ding, J. Toraskar, C. Chui, L. L. Anderson, and D. Nori. "Computation of radiation dose distributions for shielded cervical applicators." International Journal of Radiation Oncology*Biology*Physics 11, no. 4 (1985): 823–30. http://dx.doi.org/10.1016/0360-3016(85)90317-7.

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13

Sopasakis, Pantelis, and Haralambos Sarimveis. "An integer programming approach for optimal drug dose computation." Computer Methods and Programs in Biomedicine 108, no. 3 (2012): 1022–35. http://dx.doi.org/10.1016/j.cmpb.2012.06.008.

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14

Hounsell, A. R., and J. M. Wilkinson. "Data For Dose Computation In Treatments With Multileaf Collimators." Journal of Medical Physics 16, no. 2 (1991): 32. http://dx.doi.org/10.4103/0971-6203.50166.

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15

Magro, Giuseppe, Stewart Mein, Benedikt Kopp, et al. "FRoG dose computation meets Monte Carlo accuracy for proton therapy dose calculation in lung." Physica Medica 86 (June 2021): 66–74. http://dx.doi.org/10.1016/j.ejmp.2021.05.021.

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16

Beam, Andrew L., and Alison A. Motsinger-Reif. "Optimization of Nonlinear Dose- and Concentration-Response Models Utilizing Evolutionary Computation." Dose-Response 9, no. 3 (2010): dose—response.0. http://dx.doi.org/10.2203/dose-response.09-030.beam.

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17

Daartz, J., T. Madden, E. Cascio, A. Lalonde, and J. P. Schuemann. "Computation of Voxel-by-Voxel Dose Rates in Patients for Proton Pencil Beam Dose Delivery." International Journal of Radiation Oncology*Biology*Physics 114, no. 3 (2022): S140—S141. http://dx.doi.org/10.1016/j.ijrobp.2022.07.606.

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18

Wu, X., J. Y. Ting, A. M. Markoe, H. J. Landy, J. A. Fiedler, and J. Russell. "Stereotactic Dose Computation and Plan Optimization Using the Convolution Theorem." Stereotactic and Functional Neurosurgery 66, no. 1 (1996): 302–8. http://dx.doi.org/10.1159/000099822.

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19

Wang, Yangping, Chong Deng, Lian Li, and Jianwu Dang. "Compute Unified Device Architecture-Based Parallel Dose-Volume Histogram Computation." Journal of Medical Imaging and Health Informatics 5, no. 4 (2015): 833–40. http://dx.doi.org/10.1166/jmihi.2015.1466.

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20

Möller, T. R., U. Rosenow, R. E. Bentley, et al. "5. Computation of the Absorbed Dose Distribution in a Patient." Reports of the International Commission on Radiation Units and Measurements os-22, no. 1 (1987): 19–29. http://dx.doi.org/10.1093/jicru_os22.1.19.

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21

Möller, T. R., U. Rosenow, R. E. Bentley, et al. "5. Computation of the Absorbed Dose Distribution in a Patient." Journal of the International Commission on Radiation Units and Measurements os22, no. 1 (1987): 19–29. http://dx.doi.org/10.1093/jicru/os22.1.19.

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22

Elbern, Alwin W. "Computation of dose distribution for linear radioactive sources in brachytherapy." Computers in Biology and Medicine 22, no. 4 (1992): 263–68. http://dx.doi.org/10.1016/0010-4825(92)90065-u.

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23

Jacques, R., R. Taylor, J. Wong, and T. McNutt. "SU-GG-T-604: GPU-Accelerated KV/MV Dose Computation." Medical Physics 37, no. 6Part25 (2010): 3326. http://dx.doi.org/10.1118/1.3469005.

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24

Ambrožič, Klemen, Rosaria Vilarri, Paola Batistoni, and Luka Snoj. "APPLICATION OF THE JSIR2S CODE PACKAGE FOR SHUTDOWN DOSE RATE CALCULATIONS ON JET." EPJ Web of Conferences 247 (2021): 06050. http://dx.doi.org/10.1051/epjconf/202124706050.

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In this paper we present a computational exercise for shut-down dose rate calculations for the JET tokamak using the in-house developed JSIR2S code package as part of its validation. The computation is performed in two parts: neutron transport and transport of secondary gamma radiation. In order to calculate neutron activation reaction rates with sufficiently low variance, hybrid variance reduction techniques using the ADVANTG code have been utilized. Probability based sampling of secondary source particles was performed. Calculated gamma dose rates after shut down are compared with dose rate
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25

Mettivier, Giovanni, Antonio Sarno, Youfang Lai, et al. "Virtual Clinical Trials in 2D and 3D X-ray Breast Imaging and Dosimetry: Comparison of CPU-Based and GPU-Based Monte Carlo Codes." Cancers 14, no. 4 (2022): 1027. http://dx.doi.org/10.3390/cancers14041027.

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Computational reproductions of medical imaging tests, a form of virtual clinical trials (VCTs), are increasingly being used, particularly in breast imaging research. The accuracy of the computational platform that is used for the imaging and dosimetry simulation processes is a fundamental requirement. Moreover, for practical usage, the imaging simulation computation time should be compatible with the clinical workflow. We compared three different platforms for in-silico X-ray 3D breast imaging: the Agata (University & INFN Napoli) that was based on the Geant4 toolkit and running on a CPU-b
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26

Lobach, S. Yu, O. V. Sevastyuk, and V. I. Slisenko. "Computation of the radiation characteristics of spent fuel of the RBMK-1000 type reactor." Nuclear Physics and Atomic Energy 5, no. 2 (2004): 71–76. https://doi.org/10.15407/jnpae2004.02.071.

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Evaluative computation results of residual energy-release and exposure dose rate are presented. Computation was performed for the RBMK-1000 spent fuel assembly with the average and maximum burn-up and various initial enrichments by means of the computer code SAS2H from the package SCALE.
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27

Ahmed, Mohammed Shareef. "Radiotherapy Treatment Planning With Dose Volume Constraints By Linear Programming Approach." Journal of Progressive Research in Mathematics 9, no. 2 (2016): 1381–88. https://doi.org/10.5281/zenodo.3976736.

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Optimization has become an important tool in treatment planning for cancer radiation therapy. It may be used to determine beam weights, beam directions, and appropriate use of beam modifiers such as wedges and blocks, with the aim of delivering a required dose to the tumor while sparing nearby critical structures and normal tissue. Linear programming formulations are a core computation in many approaches to treatment planning, because of the abundance of highly developed linear programming software. Moreover the choices of formulation, algorithm, and pivot rule that perform best from a computa
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28

Lin, Ruitao, Yanhong Zhou, Fangrong Yan, Daniel Li, and Ying Yuan. "BOIN12: Bayesian Optimal Interval Phase I/II Trial Design for Utility-Based Dose Finding in Immunotherapy and Targeted Therapies." JCO Precision Oncology, no. 4 (November 2020): 1393–402. http://dx.doi.org/10.1200/po.20.00257.

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PURPOSE For immunotherapy, such as checkpoint inhibitors and chimeric antigen receptor T-cell therapy, where the efficacy does not necessarily increase with the dose, the maximum tolerated dose may not be the optimal dose for treating patients. For these novel therapies, the objective of dose-finding trials is to identify the optimal biologic dose (OBD) that optimizes patients’ risk-benefit trade-off. METHODS We propose a simple and flexible Bayesian optimal interval phase I/II (BOIN12) trial design to find the OBD that optimizes the risk-benefit trade-off. The BOIN12 design makes the decision
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29

Mishev, Alexander, Sasu Tuohino, and Ilya Usoskin. "Neutron monitor count rate increase as a proxy for dose rate assessment at aviation altitudes during GLEs." Journal of Space Weather and Space Climate 8 (2018): A46. http://dx.doi.org/10.1051/swsc/2018032.

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Radiation exposure due to cosmic rays, specifically at cruising aviation altitudes, is an important topic in the field of space weather. While the effect of galactic cosmic rays can be easily assessed on the basis of recent models, estimate of the dose rate during strong solar particle events is rather complicated and time consuming. Here we compute the maximum effective dose rates at a typical commercial flight altitude of 35 kft (≈11 000 m above sea level) during ground level enhancement events, where the necessary information, namely derived energy/rigidity spectra of solar energetic partic
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30

Sullivan, A., and M. Brand. "SU-E-T-806: Very Fast GPU-Based IMPT Dose Computation." Medical Physics 42, no. 6Part25 (2015): 3523. http://dx.doi.org/10.1118/1.4925170.

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31

Jelen, U., M. Radon, A. Santiago, A. Wittig, and F. Ammazzalorso. "A Monte Carlo tool for raster-scanning particle therapy dose computation." Journal of Physics: Conference Series 489 (March 24, 2014): 012013. http://dx.doi.org/10.1088/1742-6596/489/1/012013.

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32

Rout, Sabyasachi, D. G. Mishra, P. M. Ravi, Vandana Pulhani, and R. M. Tripathi. "RADCOM: Radiation dose computation model- a software for radiological impact assessment." Progress in Nuclear Energy 118 (January 2020): 103141. http://dx.doi.org/10.1016/j.pnucene.2019.103141.

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33

Jacques, Robert, John Wong, Russell Taylor, and Todd McNutt. "Real-time dose computation: GPU-accelerated source modeling and superposition/convolution." Medical Physics 38, no. 1 (2010): 294–305. http://dx.doi.org/10.1118/1.3483785.

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34

Tripathi, H. B. "A General Formulation For Depth Dose Computation In Photon Beam Dosimetry." Journal of Medical Physics 11, no. 3 (1986): 12. http://dx.doi.org/10.4103/0971-6203.50285.

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35

Böhlen, T. T., R. Dreindl, J. Osorio, G. Kragl, and M. Stock. "PO-0800: Log file based performance characterization of a PBS dose delivery system with dose re-computation." Radiotherapy and Oncology 123 (May 2017): S426—S427. http://dx.doi.org/10.1016/s0167-8140(17)31237-9.

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36

Liang, J., D. Yan, and Y. Chi. "SU-GG-T-36: Influence of Dose Grid Resolution in Cumulative Dose Computation for 4D Inverse Planning." Medical Physics 37, no. 6Part15 (2010): 3192. http://dx.doi.org/10.1118/1.3468422.

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37

Meer, Marjolein C., Peter A. N. Bosman, Bradley R. Pieters, et al. "Sensitivity of dose‐volume indices to computation settings in high‐dose‐rate prostate brachytherapy treatment plan evaluation." Journal of Applied Clinical Medical Physics 20, no. 4 (2019): 66–74. http://dx.doi.org/10.1002/acm2.12563.

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38

Satoh, Daiki, Hiromasa Nakayama, Takuya Furuta, Tamotsu Yoshihiro, and Kensaku Sakamoto. "Simulation code for estimating external gamma-ray doses from a radioactive plume and contaminated ground using a local-scale atmospheric dispersion model." PLOS ONE 16, no. 1 (2021): e0245932. http://dx.doi.org/10.1371/journal.pone.0245932.

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In this study, we developed a simulation code powered by lattice dose-response functions (hereinafter SIBYL), which helps in the quick and accurate estimation of external gamma-ray doses emitted from a radioactive plume and contaminated ground. SIBYL couples with atmospheric dispersion models and calculates gamma-ray dose distributions inside a target area based on a map of activity concentrations using pre-evaluated dose-response functions. Moreover, SIBYL considers radiation shielding due to obstructions such as buildings. To examine the reliability of SIBYL, we investigated five typical cas
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39

Zhang, Libo, Benqiang Yang, Zhikun Zhuang, et al. "Optimized Parallelization for Nonlocal Means Based Low Dose CT Image Processing." Computational and Mathematical Methods in Medicine 2015 (2015): 1–11. http://dx.doi.org/10.1155/2015/790313.

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Low dose CT (LDCT) images are often significantly degraded by severely increased mottled noise/artifacts, which can lead to lowered diagnostic accuracy in clinic. The nonlocal means (NLM) filtering can effectively remove mottled noise/artifacts by utilizing large-scale patch similarity information in LDCT images. But the NLM filtering application in LDCT imaging also requires high computation cost because intensive patch similarity calculation within a large searching window is often required to be used to include enough structure-similarity information for noise/artifact suppression. To impro
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40

Devine, R. T. "Computation of cross sections and dose conversion factors for criticality accident dosimetry." Radiation Protection Dosimetry 110, no. 1-4 (2004): 491–95. http://dx.doi.org/10.1093/rpd/nch381.

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41

Guo, Jiahao, Xinlei Li, Yidi Wang, et al. "Application of phase space file secondary computation method in cell dose distribution." Radiation Physics and Chemistry 226 (January 2025): 112301. http://dx.doi.org/10.1016/j.radphyschem.2024.112301.

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42

Sechopoulos, Ioannis, Sankararaman Suryanarayanan, Srinivasan Vedantham, Carl D'Orsi, and Andrew Karellas. "Computation of the glandular radiation dose in digital tomosynthesis of the breast." Medical Physics 34, no. 1 (2006): 221–32. http://dx.doi.org/10.1118/1.2400836.

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43

Alber, M., N. Saito, and M. Söhn. "EP-1786 Towards real-time Monte Carlo dose computation: muscle or brain?" Radiotherapy and Oncology 133 (April 2019): S966—S967. http://dx.doi.org/10.1016/s0167-8140(19)32206-6.

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44

Mejaddem, Y., Dž Belkić, A. Brahme, and S. Hyödynmaa. "Development of the electron transport theory and absorbed dose computation in matter." Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms 187, no. 4 (2002): 499–524. http://dx.doi.org/10.1016/s0168-583x(01)01156-9.

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45

Beilla, Sara, Tony Younes, Laure Vieillevigne, Manuel Bardies, Xavier Franceries, and Luc Simon. "Monte-Carlo dose computation in radiotherapy for lung at very low density." Physica Medica 32 (September 2016): 245–46. http://dx.doi.org/10.1016/j.ejmp.2016.07.519.

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46

Myronakis, Marios E., Marketa Zvelebil, and Dimitra G. Darambara. "Normalized mean glandular dose computation from mammography using GATE: a validation study." Physics in Medicine and Biology 58, no. 7 (2013): 2247–65. http://dx.doi.org/10.1088/0031-9155/58/7/2247.

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47

Chen, Z., J. Deng, D. Carlson, et al. "A Serial-imaging Based 4D Dose Computation System for Prostate Implant Dosimetry." International Journal of Radiation Oncology*Biology*Physics 75, no. 3 (2009): S349. http://dx.doi.org/10.1016/j.ijrobp.2009.07.800.

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48

Palahuta, V. M. "Computation in noise regulation." Herald of the Odessa National Maritime University, no. 75 (March 23, 2025): 176–87. https://doi.org/10.47049/2226-1893-2025-1-176-187.

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Noise is a harmful factor that poses a threat to the health of workers in many professions in the maritime industry. Domestic labour protection legislation provides effective tools for regulating the parameters of industrial noise [1]. At the same time, objective processes of globalization of the world economy, integration of Ukraine into the global system of labour division increasingly require knowledge and application of international standards in the field of occupational health. In particular, this becomes relevant in the course of training specialists to work on ships of foreign shipping
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49

Nojiri, Mai, Takushi Takata, Naonori Hu, Yoshinori Sakurai, Minoru Suzuki, and Hiroki Tanaka. "Development and evaluation of dose calculation algorithm with a combination of Monte Carlo and point-kernel methods for boron neutron capture therapy." Biomedical Physics & Engineering Express 9, no. 3 (2023): 035025. http://dx.doi.org/10.1088/2057-1976/acc33c.

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Abstract We developed a ‘hybrid algorithm’ that combines the Monte Carlo (MC) and point-kernel methods for fast dose calculation in boron neutron capture therapy. The objectives of this study were to experimentally verify the hybrid algorithm and to verify the calculation accuracy and time of a ‘complementary approach’ adopting both the hybrid algorithm and the full-energy MC method. In the latter verification, the results were compared with those obtained using the full-energy MC method alone. In the hybrid algorithm, the moderation process of neutrons is simulated using only the MC method, a
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50

TAKAHASHI, KENICHI, HIDEYO ISHIGAKI, KIMIO UDAGAWA, MASAMI SAITO, and KYOKO YAMAGUCHI. "COMPUTATION OF DOSE DISTRIBUTION BY A PERSONAL COMPUTER FOR THE EXTERNAL BEAM IRRADIATION." Japanese Journal of Radiological Technology 43, no. 10 (1987): 1529–35. http://dx.doi.org/10.6009/jjrt.kj00001363744.

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