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https://doi.org/10.1117/3.2605...
Part of book or chapter of book . 2022 . Peer-reviewed
Data sources: Crossref
https://doi.org/10.1117/3.2197...
Part of book or chapter of book . 2015 . Peer-reviewed
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https://doi.org/10.1117/3.8173...
Part of book or chapter of book . 2009 . Peer-reviewed
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Computer Simulation and Analysis

Authors: Jiang Hsieh;

Computer Simulation and Analysis

Abstract

8.1 What Is Computer Simulation? Computer simulation uses theoretical models to predict the performance of a real system. Computer simulation can be divided into two general categories: analytical and statistical. Analytically based simulation generates system models using known analytical equations. A good example of this category is the generation of projections of mathematical phantoms. This type of projection is calculated based on the line integrals of attenuation coefficients of objects whose shapes can be described by closed-form equations (the phantom is formed with cylinders, spheres, ellipsoids, or bars). For a given source and detector cell position, the line integral can be calculated precisely for each object. The final result is the weighted summation of these integrals. Statistically based simulation, on the other hand, uses random number generators and the physical property of the interaction process to predict the system performance. A good example is the Monte Carlo simulation used to predict the scatter distribution. Computer simulation is applicable in two major areas: system optics and system physics. System optics mainly addresses issues related to the geometric factors of the system. For example, computer simulation is helpful in understanding the impact of x-ray focal spot size, detector size, source-to-detector distance, and source-to-iso distance to the system spatial resolution. In our analyses, we focus mainly on the geometric factors that impact the system performance. System physics focuses on the physics properties of each process. For example, we can use a known input x-ray spectrum, the attenuation characteristics of different materials as a function of the x-ray energy, and the relative concentration of each material to understand the beam-hardening phenomenon and its impact on image quality. Physics-based simulation can also help to explain the impact of component characteristics on system performance parameters, such as LCD. For each application category (optics or physics), either analytical or statistical simulation tools can be used. Computer simulation is a useful tool for designing a new CT system. During the design process, the designer is often faced with the problem of determining various system parameters.

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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