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An update on computational anthropomorphic anatomical models

  • Azadeh Akhavanallaf
  • , Hadi Fayad
  • , Yazdan Salimi
  • , Antar Aly
  • , Hassan Kharita
  • , Huda Al Naemi
  • , Habib Zaidi*
  • *Corresponding author for this work
  • Geneva University Hospitals
  • Hamad Medical Corporation
  • Weill Cornell Medical College in Qatar
  • University of Geneva
  • University of Groningen

Research output: Contribution to journal › Journal article › Research › peer-review

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Abstract

The prevalent availability of high-performance computing coupled with validated computerized simulation platforms as open-source packages have motivated progress in the development of realistic anthropomorphic computational models of the human anatomy. The main application of these advanced tools focused on imaging physics and computational internal/external radiation dosimetry research. This paper provides an updated review of state-of-the-art developments and recent advances in the design of sophisticated computational models of the human anatomy with a particular focus on their use in radiation dosimetry calculations. The consolidation of flexible and realistic computational models with biological data and accurate radiation transport modeling tools enables the capability to produce dosimetric data reflecting actual setup in clinical setting. These simulation methodologies and results are helpful resources for the medical physics and medical imaging communities and are expected to impact the fields of medical imaging and dosimetry calculations profoundly.

Original languageEnglish
JournalDIGITAL HEALTH
Volume8
ISSN2055-2076
DOIs
Publication statusPublished - 2022

Bibliographical note

Publisher Copyright:
© The Author(s) 2022.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Qatar national research fund (grant number NPRP10-0126-170263) and the Medical Research Center, Hamad Medical Corporation, Doha, Qatar. We acknowledge Dr Hashem Miri and Dr Lale Rafat at Ferdowsi University of Iran for providing illustrations of their computational models. The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Qatar national research fund (grant number NPRP10-0126-170263) and the Medical Research Center, Hamad Medical Corporation, Doha, Qatar.

Keywords

  • anthropomorphic models
  • computational models
  • Human anatomy
  • medical imaging
  • Monte Carlo simulation

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