Monte Carlo methods for medical imaging research

被引：6

作者：

Lee, Hoyeon ^{[1
,2
]}

机构：

[1] Univ Hong Kong, Dept Diagnost Radiol, Hong Kong, Peoples R China

[2] Univ Hong Kong, Ctr Canc Med, Hong Kong, Peoples R China

来源：

BIOMEDICAL ENGINEERING LETTERS | 2024年 / 14卷 / 06期

关键词：

Monte Carlo; Medical imaging; Computational modeling; DIGITAL BREAST TOMOSYNTHESIS; CONE-BEAM CT; SCATTER CORRECTION; SIMULATION TOOL; CONVOLUTION SUPERPOSITION; EXPERIMENTAL-VERIFICATION; COMPUTATIONAL MODEL; COMPUTED-TOMOGRAPHY; GEANT4; SIMULATION; DOSE CALCULATIONS;

D O I：

10.1007/s13534-024-00423-x

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

In radiation-based medical imaging research, computational modeling methods are used to design and validate imaging systems and post-processing algorithms. Monte Carlo methods are widely used for the computational modeling as they can model the systems accurately and intuitively by sampling interactions between particles and imaging subject with known probability distributions. This article reviews the physics behind Monte Carlo methods, their applications in medical imaging, and available MC codes for medical imaging research. Additionally, potential research areas related to Monte Carlo for medical imaging are discussed.

引用

页码：1195 / 1205

页数：11

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