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Realistic total-body J-PET geometry optimization: Monte Carlo study.
Med Phys
January 2025
Faculty of Physics, Astronomy and Applied Computer Science, Jagiellonian University, Kraków, Poland.
Background: Total-body (TB) Positron Emission Tomography (PET) is one of the most promising medical diagnostics modalities, opening new perspectives for personalized medicine, low-dose imaging, multi-organ dynamic imaging or kinetic modeling. The high sensitivity provided by total-body technology can be advantageous for novel tomography methods like positronium imaging, demanding the registration of triple coincidences. Currently, state-of-the-art PET scanners use inorganic scintillators.
View Article and Find Full Text PDFEfficient stochastic simulation of piecewise-deterministic Markov processes and its application to the Morris-Lecar model of neural dynamics.
Biol Cybern
January 2025
Institute for Physics and Astronomy, University of Potsdam, Karl-Liebknecht-Str. 24-25, 14476, Potsdam, Germany.
Piecewise-deterministic Markov processes combine continuous in time dynamics with jump events, the rates of which generally depend on the continuous variables and thus are not constants. This leads to a problem in a Monte-Carlo simulation of such a system, where, at each step, one must find the time instant of the next event. The latter is determined by an integral equation and usually is rather slow in numerical implementation.
View Article and Find Full Text PDFMonte Carlo Simulations in Nanomedicine: Advancing Cancer Imaging and Therapy.
Nanomaterials (Basel)
January 2025
Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, ON M5G 1X6, Canada.
Monte Carlo (MC) simulations have become important in advancing nanoparticle (NP)-based applications for cancer imaging and therapy. This review explores the critical role of MC simulations in modeling complex biological interactions, optimizing NP designs, and enhancing the precision of therapeutic and diagnostic strategies. Key findings highlight the ability of MC simulations to predict NP bio-distribution, radiation dosimetry, and treatment efficacy, providing a robust framework for addressing the stochastic nature of biological systems.
View Article and Find Full Text PDFShannon Entropy Computations in Navier-Stokes Flow Problems Using the Stochastic Finite Volume Method.
Entropy (Basel)
January 2025
Faculty of Civil Engineering, Architecture and Environmental Engineering, Lodz University of Technology, 90-924 Łódź, Poland.
The main aim of this study is to achieve the numerical solution for the Navier-Stokes equations for incompressible, non-turbulent, and subsonic fluid flows with some Gaussian physical uncertainties. The higher-order stochastic finite volume method (SFVM), implemented according to the iterative generalized stochastic perturbation technique and the Monte Carlo scheme, are engaged for this purpose. It is implemented with the aid of the polynomial bases for the pressure-velocity-temperature (PVT) solutions, for which the weighted least squares method (WLSM) algorithm is applicable.
View Article and Find Full Text PDFAssessment of the effectiveness of Monte Carlo Simulation for dose control at the Moroccan Boukhalef ionization facility.
Appl Radiat Isot
January 2025
Department of Physics, Nuclear Physics and Techniques Team, Faculty of Science, Ibn Tofail University, Kenitra, Morocco.
Controlling the absorbed dose received by a target is a major challenge encountered during ionizing radiation applications. For experimentally measuring absorbed dose, dosimetric systems are used. On the other hand, in addition to experimental methods of dose measurement, there are other alternatives for calculating absorbed doses, these are numerical methods based on the Monte Carlo method which are very sophisticated and widely used throughout the world.
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