Letteratura scientifica selezionata sul tema "Dose Computation"
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Articoli di riviste sul tema "Dose Computation"
Knöös, T. "3D dose computation algorithms". Journal of Physics: Conference Series 847 (maggio 2017): 012037. http://dx.doi.org/10.1088/1742-6596/847/1/012037.
Testo completoBattista, J., J. Chen, S. Sawchuk e G. Hajdok. "Evolution of 3D X-Ray Dose Computation Algorithms". Journal of Physics: Conference Series 2630, n. 1 (1 novembre 2023): 012008. http://dx.doi.org/10.1088/1742-6596/2630/1/012008.
Testo completoCutanda Henríquez, Francisco, e Silvia Vargas Castrillón. "Confidence intervals in dose volume histogram computation". Medical Physics 37, n. 4 (15 marzo 2010): 1545–53. http://dx.doi.org/10.1118/1.3355888.
Testo completoLaub, W., M. Alber, M. Birkner e F. Nüsslin. "Monte Carlo dose computation for IMRT optimization*". Physics in Medicine and Biology 45, n. 7 (26 giugno 2000): 1741–54. http://dx.doi.org/10.1088/0031-9155/45/7/303.
Testo completoTang, Man-Lai, Karim F. Hirji e Stein E. Vollset. "Exact power computation for dose—response studies". Statistics in Medicine 14, n. 20 (30 ottobre 1995): 2261–72. http://dx.doi.org/10.1002/sim.4780142009.
Testo completoSandison, G. A., e L. S. Papiez. "Dose computation applications of the electron loss model". Physics in Medicine and Biology 35, n. 7 (1 luglio 1990): 979–97. http://dx.doi.org/10.1088/0031-9155/35/7/013.
Testo completoMohan, R., C. Chui e L. Lidofsky. "Differential pencil beam dose computation model for photons". Medical Physics 13, n. 1 (gennaio 1986): 64–73. http://dx.doi.org/10.1118/1.595924.
Testo completoSiebert, Frank-André, Ping Jiang, Rene Baumann, Gunnar Bockelmann, Susann Bohn, Maike Thieben e Jürgen Dunst. "Dose Computation of Keloids in Brachytherapy: Tg-43 or Model-Based-Dose-Calculation?" Brachytherapy 15 (maggio 2016): S149. http://dx.doi.org/10.1016/j.brachy.2016.04.262.
Testo completoDray, Nicolas, Nicolas Mary, Cédric Dossat, Jefferson Bourgoin e 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.
Testo completoPanitsa, E., J. C. Rosenwald e C. Kappas. "Developing a dose-volume histogram computation program for brachytherapy". Physics in Medicine and Biology 43, n. 8 (1 agosto 1998): 2109–21. http://dx.doi.org/10.1088/0031-9155/43/8/009.
Testo completoTesi sul tema "Dose Computation"
Jung, Haejae. "Algorithms for external beam dose computation". [Florida] : State University System of Florida, 2000. http://etd.fcla.edu/etd/uf/2000/ane5955/etd.pdf.
Testo completoTitle from first page of PDF file. Document formatted into pages; contains xii, 143 p.; also contains graphics. Vita. Includes bibliographical references (p. 140-142).
Fox, Timothy Harold. "Computation and optimization of dose distributions for rotational stereotactic radiosurgery". Diss., Georgia Institute of Technology, 1994. http://hdl.handle.net/1853/32843.
Testo completoInacio, Eloïse. "Méthodes numériques en imagerie médicale pour l'évaluation de dose per-opératoire en ablation par électroporation". Electronic Thesis or Diss., Bordeaux, 2024. http://www.theses.fr/2024BORD0474.
Testo completoAs life expectancy rises, cancer has tragically become one of the world’s leading causes of death. Among the most challenging cancers are deep-seated tumors, which are difficult to treat due to their location in vital organs like the liver or the pancreas. A promising method to tackle these tumors is electroporation ablation, which uses electric fields to create pores in the cell membranes of tumor cells. When applied with high intensity, this results in irreversible electroporation, leading to cell death without damaging nearby structures. However, electroporation requires precise planning and real-time adaptation due to its complexity. This involves numerical tools to analyze medical images and estimate the treatment area. The aim of this work is to provide such tools, analysing medical images, to per-operatively estimate the treatment area so that the interventional radiologists may adapt their approach as they are performing the procedure. More specifically, we tackle the localisation of the electrode by introducing deep learning in the existing pipeline, and the registration of the multiple scans captured during the intervention with novel auto-adaptive boundary conditions. Both computer vision tasks are crucial for a precise estimation of the electric field and need to be solved in near real time to be practical in clinical settings. These advancements in computer vision and image processing contribute to more accurate electric field estimation and improve the overall effectiveness of the procedure, leading to better patient outcomes for those battling deep-seated cancers
Vautrin, Mathias. "Planification de traitement en radiothérapie stéréotaxique par rayonnement synchrotron. Développement et validation d'un module de calcul de dose par simulations Monte Carlo". Phd thesis, Université de Grenoble, 2011. http://tel.archives-ouvertes.fr/tel-00641325.
Testo completoNygren, Nelly. "Optimization of the Gamma Knife Treatment Room Design". Thesis, KTH, Fysik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-300904.
Testo completoStrålsäkerhet är en viktig aspekt vid uppförandet av behandlingsrum för strål-terapisystem. Strålningsnivåerna som sjukvårdspersonal och allmänheten kan exponeras för utanför behandlingsrummet regleras av myndigheter och påverkar vilken väggtjocklek som behövs och vilka platser som är lämpliga att placera systemen på. Flertalet metoder för strålskyddsberäkning existerar, men de är inte väl anpassade till det stereotaktiska radiokirurgiska systemet Leksell Gamma Knife, eftersom det har ett inbyggt strålskydd. Det inbyggda strålskyddet gör att strålfältet runt Gamma Knife är anisotropt och generellt har lägre energi än primärstrålningen från systemets koboltkällor. Förenklingar som görs rörande strålfältet i flera existerande metoder för strålskyddsberäkning kan leda till att överdrivet tjocka strålskydd används eller begränsa antalet lämpliga platser att placera systemet på. I detta projekt utvecklades en dosberäkningsalgoritm, som i två steg använder data genererad genom Monte Carlo-simuleringar. Algoritmen använder ett fasrum för att detaljerat beskriva strålfältet runt Gamma Knife. Information om enskilda fotoner i fältet används sen i kombination med ett genererat bibliotek av data som beskriver det dosbidrag som en foton bidrar med utanför behandlingsrummet, baserat på fotonens energi och väggarnas tjocklek. Dosberäkningsalgoritmen är snabb nog att integreras i optimeringsprocesser där den används iterativt samtidigt som rumsdesignparametrar varieras. I denna rapport demonstreras ett fall med ett rum av bestämd storlek, där positionen av Gamma Knife i rummet och väggarnas tjocklekar varieras. Optimeringens syfte i exemplet är att hitta den rumsdesign som med de minsta väggtjocklekarna resulterar i acceptabla strålningsnivåer utanför rummet. Resultaten tyder på att dosberäkningsalgoritmen sannolikt kan användas i mer komplexa optimeringar med fler designvariabler och mer avancerade designmål.
Morén, Björn. "Mathematical Modelling of Dose Planning in High Dose-Rate Brachytherapy". Licentiate thesis, Linköpings universitet, Optimeringslära, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-154966.
Testo completoAspradakis, Maria M. "A study to assess and improve dose computations in photon beam therapy". Thesis, University of Edinburgh, 1997. http://hdl.handle.net/1842/21334.
Testo completoOLIVEIRA, JUNIOR Wilson Rosa de. "Turing´s analysis of computation and artificial neural network". Universidade Federal de Pernambuco, 2004. https://repositorio.ufpe.br/handle/123456789/1970.
Testo completoConselho Nacional de Desenvolvimento Científico e Tecnológico
Inspirado por uma sugestão de McCulloch e Pitts em seu trabalho pioneiro, uma simulação de Máquinas de Turing (MT) por Redes Neurais Artifiais (RNAs) apresentada. Diferente dos trabalhos anteriores, tal simulação está de acordo com a interpretação correta da análise de Turing sobre computação; é compatvel com as abordagens correntes para análise da cognição como um processo interativo agente-ambiente; e é fisicamente realizável uma vez que não se usa pesos nas conexãos com precisão ilimitada. Uma descrição completa de uma implementação de uma MT universal em uma RNA recorrente do tipo sigmóide é dada. A fita, um recurso infinito, é deixada fora da codificação como uma caracterstica externa não-intrínsica. A rede resultante é chamada de Máquina de Turing Neural. O modelo clássico de computação Máquina de Turing = Fita + Autômato de Estados Finito (AEF) é trocado pelo modelo de computação neural Máquina de Turing Neural (MTN) = Fita + Rede Neural Artifial (RNA) Argumentos para plausabilidade física e cognitiva desta abordagem são fornecidos e as consequências matemáticas são investigadas. E bastante conhecido na comunidade de neurocomputação teórica, que um AEF arbitrário não pode ser implementado em uma RNA quando ruído ou limite de precisão é considerado: sob estas condições, sistemas analógicos em geral, e RNA em particular, são computacionalmente equivalentes aos Autômatos Definidos uma classe muita restrita de AEF. Entre as principais contribuições da abordagem proposta é a definição de um novo modelo de máquina, Máquina de Turing Definida(MTD), que surge quando ruído é levado em consideração. Este resultado reflete na segunda equação descrita acima se tornando MTN com ruíıdo (MTN) = Fita + RNA com ruído(RNA) com a equação correspondente Máquina de Turing Definida = Fita + Autômatos Finitos Definidos (AFD) A investigação de capacidades computacionais das Máquinas de Turing Definida é uma outra contribuição importante da Tese. É provado que elas computam a classe das funções elementares (Brainerd & Landweber, 1974) da Teoria da Recursão
Palit, Robin. "Computational Tools and Methods for Objective Assessment of Image Quality in X-Ray CT and SPECT". Diss., The University of Arizona, 2012. http://hdl.handle.net/10150/268492.
Testo completoMoura, Augusto Fontan. "A computational study of the airflow at the intake region of scramjet engines". Instituto Tecnológico de Aeronáutica, 2014. http://www.bd.bibl.ita.br/tde_busca/arquivo.php?codArquivo=2973.
Testo completoLibri sul tema "Dose Computation"
D, Sawant Pramilla, e Bhabha Atomic Research Centre, a cura di. Manual on internal dose computation and reporting. Mumbai: Bhabha Atomic Research Centre, 1999.
Cerca il testo completoUnited States. Defense Nuclear Agency, a cura di. FIIDOS--a computer code for the computation of fallout inhalation and ingestion dose to organs: Computer user's guide. Washington, D.C: Defense Nuclear Agency, 1985.
Cerca il testo completo1957-, Jackson Thomas L., e Joslin R. D. 1963-, a cura di. Theory and computation in hydrodynamic stability. Cambridge: Cambridge University Press, 2003.
Cerca il testo completo1934-, Jameson Antony, Caughey D. A e Hafez M. M, a cura di. Frontiers of computational fluid dynamics 1994. Chichester: Wiley, 1994.
Cerca il testo completo1940-, Jäger W., Rannacher Rolf e Warnatz J, a cura di. Reactive flows, diffusion and transport: From experiments via mathematical modeling to numerical simulation and optimization : final report of SFB (Collaborative Research Center) 359. Berlin: Springer, 2007.
Cerca il testo completoChakrabarti, Anirban. Grid computing security. Berlin: Springer, 2010.
Cerca il testo completoTuncer, Cebeci, a cura di. Computational fluid dynamics for engineers: From panel to Navier-Stokes methods with computer programs. Long Beach, Calif: Horizons Pub. Inc., 2005.
Cerca il testo completoBattista, Jerry. Introduction to Megavoltage X-Ray Dose Computation Algorithms. Taylor & Francis Group, 2019.
Cerca il testo completoIntroduction to Megavoltage X-Ray Dose Computation Algorithms. Taylor & Francis Group, 2019.
Cerca il testo completoBattista, Jerry. Introduction to Megavoltage X-Ray Dose Computation Algorithms. Taylor & Francis Group, 2019.
Cerca il testo completoCapitoli di libri sul tema "Dose Computation"
Rosenwald, J. C. "Framework for Computation of Patient Dose Distribution". In Handbook of Radiotherapy Physics, Vol1:557—Vol1:564. 2a ed. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9780429201493-33.
Testo completoDo, Synho, Janne J. Näppi e Hiroyuki Yoshida. "Iterative Reconstruction for Ultra-Low-Dose Laxative-Free CT Colonography". In Abdominal Imaging. Computation and Clinical Applications, 99–106. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-41083-3_12.
Testo completoLaub, W., M. Alber, M. Birkner e F. Nüsslin. "IMRT with Monte Carlo dose computation: what is the benefit?" In The Use of Computers in Radiation Therapy, 423–24. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-642-59758-9_160.
Testo completoNahum, Alan, e J. C. Rosenwald. "Monte-Carlo and Grid-Based-Deterministic Models for Patient Dose Computation". In Handbook of Radiotherapy Physics, Vol1:603—Vol1:628. 2a ed. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9780429201493-36.
Testo completoAbdennhader, Nabil, Mohamed Ben Belgacem, Raphaël Couturier, David Laiymani, Sébastien Miquée, Marko Niinimaki e Marc Sauget. "Gridification of a Radiotherapy Dose Computation Application with the XtremWeb-CH Environment". In Advances in Grid and Pervasive Computing, 188–97. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20754-9_20.
Testo completoKim, Chang-Won, Jong-Hyo Kim, Hyunna Lee, Jeongjin Lee, Se-Hyung Kim, Zepa Yang e Yeong-Gil Shin. "Application of Synthetic Sinogram Based Low-Dose CT Simulation and Fold-Preserving Electronic Cleansing Technique for CT Colonography". In Abdominal Imaging. Computation and Clinical Applications, 89–98. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-41083-3_11.
Testo completoTo, Karen CY, e K. Scott Brimble. "Factors Affecting Peritoneal Dialysis Dose". In Studies in Computational Intelligence, 1477–535. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-27558-6_15.
Testo completoUhlin, Fredrik, e Ivo Fridolin. "Optical Monitoring of Dialysis Dose". In Studies in Computational Intelligence, 867–928. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-27558-6_3.
Testo completoSalvador, Ricardo, Dennis Q. Truong, Marom Bikson, Alexander Opitz, Jacek Dmochowski e Pedro C. Miranda. "Role of Computational Modeling for Dose Determination". In Practical Guide to Transcranial Direct Current Stimulation, 233–62. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-95948-1_9.
Testo completoBruda, Stefan D., e Mary Sarah Ruth Wilkin. "Emergence in Context-Free Parallel Communicating Grammar Systems: What Does and Does not Make a Grammar System More Expressive Than Its Parts". In Emergent Computation, 171–213. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46376-6_8.
Testo completoAtti di convegni sul tema "Dose Computation"
Tani, A. A., J. M. Norberto, M. R. da Silva e A. Durand-Petiteville. "Automated computation of cutting paths for unit-dose repackaging of pharmaceutical blister packs". In 2024 IEEE 20th International Conference on Automation Science and Engineering (CASE), 1678–83. IEEE, 2024. http://dx.doi.org/10.1109/case59546.2024.10711355.
Testo completoKuhn, Alexander, Benjamin Kutz, Tobias Günther e Andreas Rumpf. "Numerical Examination of a Model Rotor in Brownout Conditions". In Vertical Flight Society 70th Annual Forum & Technology Display, 1–12. The Vertical Flight Society, 2014. http://dx.doi.org/10.4050/f-0070-2014-9437.
Testo completoYu, Wei, Xiaolin Wang, Nan Qin, Hongchi Zhou, Runze Xu, Jiafu Gao e Yalun Wang. "Low-dose CT image processing based on controllable residual U-shaped network". In 2024 International Applied Computational Electromagnetics Society Symposium (ACES-China), 1–3. IEEE, 2024. http://dx.doi.org/10.1109/aces-china62474.2024.10699581.
Testo completoBarbour, Robert, David Corne e John McCall. "Accelerated optimisation of chemotherapy dose schedules using fitness inheritance". In 2010 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2010. http://dx.doi.org/10.1109/cec.2010.5586118.
Testo completoWang, Dongmei, Yiwen Liang, Chengyu Tan, Hongbin Dong e Xinmin Yang. "Pathogen dose based natural killer cell algorithm for classification". In GECCO '21: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3449726.3459434.
Testo completoWitten, Matthew, e Owen Clancey. "An evolutionary algorithm for optimization of affine transformation parameters for dose matrix warping in patient-specific quality assurance of radiotherapy dose distributions". In 2012 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2012. http://dx.doi.org/10.1109/cec.2012.6256139.
Testo completoTao, Yanyun, Yuzhen Zhang e Bin Jiang. "Evolutionary learning-based modeling for warfarin dose prediction in Chinese". In GECCO '17: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3067695.3082492.
Testo completoConnor, Mark, e Michael O'Neill. "Optimizing the parameters of a physical exercise dose-response model". In GECCO '21: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3449726.3459494.
Testo completoWitten, Matthew, e Owen Clancey. "Residual dose deviation differential histogram analysis using evolutionary-optimized transform parameters for dose distribution warping in patient-specific quality assurance in external beam radiation therapy". In 2017 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2017. http://dx.doi.org/10.1109/cec.2017.7969506.
Testo completoZhang, Qi, Heli Gong, Liye Liu, Yushou Song, Qinjian Cao, Jinlong Yong e Jiawen Hu. "Research on Monte Carlo-Neutron Point Kernel Integration Method Coupling Calculation Method of Neutron Radiation Field". In 2024 31st International Conference on Nuclear Engineering. American Society of Mechanical Engineers, 2024. http://dx.doi.org/10.1115/icone31-135218.
Testo completoRapporti di organizzazioni sul tema "Dose Computation"
Breazeal, N. L., K. R. Davis, R. A. Watson, D. S. Vickers e M. S. Ford. Simulation-based computation of dose to humans in radiological environments. Office of Scientific and Technical Information (OSTI), marzo 1996. http://dx.doi.org/10.2172/206637.
Testo completoDudley A, III Egbert, John H. Case Stephen D. Stiver e Raine David. FIIDOS--A Computer Code for the Computation of Fallout Inhalation and Ingestion Dose to Organs Computer User's Guide (Revision 4). Fort Belvoir, VA: Defense Technical Information Center, maggio 2007. http://dx.doi.org/10.21236/ada469466.
Testo completoRittmann, P. D. Emergency Doses (ED) - Revision 3: A calculator code for environmental dose computations. Office of Scientific and Technical Information (OSTI), dicembre 1990. http://dx.doi.org/10.2172/6040411.
Testo completoScott, Bobby, R., Ph.D. Advanced Computational Approaches for Characterizing Stochastic Cellular Responses to Low Dose, Low Dose Rate Exposures. Office of Scientific and Technical Information (OSTI), giugno 2003. http://dx.doi.org/10.2172/812039.
Testo completoMarcath, Matthew, Douglas Mayo, Joshua Spencer, Tucker McClanahan e Lucas Hetrick. Evaluation of Attila and MCNP computational methods for dose and exposure estimation. Office of Scientific and Technical Information (OSTI), settembre 2021. http://dx.doi.org/10.2172/1821360.
Testo completoAuthor, Not Given. DOE National Laboratories' Computational Facilities - Research Workshop Report. Office of Scientific and Technical Information (OSTI), febbraio 2020. http://dx.doi.org/10.2172/1601798.
Testo completoPeñaloza, Rafael, e Anni-Yasmin Turhan. Completion-based computation of least common subsumers with limited role-depth for EL and Prob-EL⁰¹. Technische Universität Dresden, 2010. http://dx.doi.org/10.25368/2022.175.
Testo completoNapier, B. A. Computational model design specification for Phase 1 of the Hanford Environmental Dose Reconstruction Project. Office of Scientific and Technical Information (OSTI), luglio 1991. http://dx.doi.org/10.2172/5582525.
Testo completoWallace, Susan S. DOE EPSCoR Initiative in Structural and computational Biology/Bioinformatics. Office of Scientific and Technical Information (OSTI), febbraio 2008. http://dx.doi.org/10.2172/924036.
Testo completoNone, None. DOE Computational Science Graduate Fellowship (CSGF) Grant 2019 Cohort. Office of Scientific and Technical Information (OSTI), dicembre 2023. http://dx.doi.org/10.2172/2229639.
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