Modeling<unk>  propagation with<unk><unk><unk> s is a flexible yet rigorous approach to simulate<unk><unk> . In the<unk> , local rules of<unk><unk>  are expressed as probability distributions which describe the step size of<unk>  movement between sites of<unk> -matter interaction and the angles of deflection in a<unk> 's trajectory when a scattering event occurs. This is equivalent to modeling<unk><unk>  analytically by the radiative transfer equation (RTE), which describes the motion of<unk> s using a differential equation. However, closed-form solutions of the RTE are often not possible; for some geometries, the diffusion approximation can be used to simplify the RTE, although this, in turn, introduces many inaccuracies, especially near sources and boundaries. In contrast,<unk><unk>  simulations can be made arbitrarily accurate by increasing the number of<unk> s traced. For example, see the movie, where a<unk><unk>  simulation of a pencil beam incident on a semi-infinite medium models both the initial ballistic<unk>  flow and the later diffuse propagation. The<unk><unk><unk>  is necessarily statistical and therefore requires significant computation time to achieve precision. In addition<unk><unk>  simulations can keep track of multiple physical quantities simultaneously, with any desired spatial and temporal resolution. This flexibility makes<unk><unk>  modeling a powerful tool. Thus, while computationally inefficient,<unk><unk><unk> s are often considered the standard for simulated measurements of<unk><unk>  for many biomedical applications.<unk><unk>  simulation of a pencil beam incident on a semi-infinite scattering medium.
Monte Carlo method for photon transport
Automated tissue image analysis
Epidemiology data for low-linear energy transfer radiation
History of Modern Biomedicine Research Group
Micropore particle technology
Measures of pollutant concentration
Modified Maddrey's discriminant function
Dose verification system