Monte Carlo methods for medical imaging research

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 interact...

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Published inBiomedical engineering letters Vol. 14; no. 6; pp. 1195 - 1205
Main Author Lee, Hoyeon
Format Journal Article
LanguageEnglish
Published Korea The Korean Society of Medical and Biological Engineering 01.11.2024
Springer Nature B.V
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Online AccessGet full text
ISSN2093-9868
2093-985X
2093-985X
DOI10.1007/s13534-024-00423-x

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Abstract 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.
AbstractList 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.
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.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.
Author Lee, Hoyeon
Author_xml – sequence: 1
  givenname: Hoyeon
  orcidid: 0000-0002-1165-1509
  surname: Lee
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  email: hlee01@hku.hk
  organization: Department of Diagnostic Radiology and Centre of Cancer Medicine, University of Hong Kong
BackLink https://www.ncbi.nlm.nih.gov/pubmed/39465109$$D View this record in MEDLINE/PubMed
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Issue 6
Keywords Monte Carlo
Computational modeling
Medical imaging
Language English
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SubjectTerms Algorithms
Biological and Medical Physics
Biomedical Engineering and Bioengineering
Biomedicine
Biophysics
Computer applications
Engineering
Medical and Radiation Physics
Medical imaging
Medical research
Monte Carlo simulation
Review
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Title Monte Carlo methods for medical imaging research
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