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 in | Biomedical engineering letters Vol. 14; no. 6; pp. 1195 - 1205 |
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| Main Author | |
| Format | Journal Article |
| Language | English |
| Published |
Korea
The Korean Society of Medical and Biological Engineering
01.11.2024
Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
| ISSN | 2093-9868 2093-985X 2093-985X |
| DOI | 10.1007/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. |
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| 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 fullname: Lee, Hoyeon 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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| CitedBy_id | crossref_primary_10_2298_NTRP2403212Z crossref_primary_10_3390_nano15020117 crossref_primary_10_1088_2057_1976_adba65 |
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| Keywords | Monte Carlo Computational modeling Medical imaging |
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| Title | Monte Carlo methods for medical imaging research |
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