• Nuclear Engineering and Technology
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• 제38권3호
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• pp.239-250
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• 2006

Computational anthropomorphic phantoms are computer models of human anatomy used in the calculation of radiation dose distribution in the human body upon exposure to a radiation source. Depending on the manner to represent human anatomy, they are categorized into two classes: stylized and tomographic phantoms. Stylized phantoms, which have mainly been developed at the Oak Ridge National Laboratory (ORNL), describe human anatomy by using simple mathematical equations of analytical geometry. Several improved stylized phantoms such as male and female adults, pediatric series, and enhanced organ models have been developed following the first hermaphrodite adult stylized phantom, Medical Internal Radiation Dose (MIRD)-5 phantom. Although stylized phantoms have significantly contributed to dosimetry calculation, they provide only approximations of the true anatomical features of the human body and the resulting organ dose distribution. An alternative class of computational phantom, the tomographic phantom, is based upon three-dimensional imaging techniques such as magnetic resonance (MR) imaging and computed tomography (CT). The tomographic phantoms represent the human anatomy with a large number of voxels that are assigned tissue type and organ identity. To date, a total of around 30 tomographic phantoms including male and female adults, pediatric phantoms, and even a pregnant female, have been developed and utilized for realistic radiation dosimetry calculation. They are based on MRI/CT images or sectional color photos from patients, volunteers or cadavers. Several investigators have compared tomographic phantoms with stylized phantoms, and demonstrated the superiority of tomographic phantoms in terms of realistic anatomy and dosimetry calculation. This paper summarizes the history and current status of both stylized and tomographic phantoms, including Korean computational phantoms. Advantages, limitations, and future prospects are also discussed.

• 한국의학물리학회:학술대회논문집
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• 한국의학물리학회 2006년도 제33회 추계학술대회 발표논문집
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• pp.127-127
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• 2006

• Journal of Radiation Protection and Research
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• 제47권3호
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• pp.111-133
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• 2022

The exciting advancement related to the "modeling of digital human" in terms of a computational phantom for radiation dose calculations has to do with the latest hype related to deep learning. The advent of deep learning or artificial intelligence (AI) technology involving convolutional neural networks has brought an unprecedented level of innovation to the field of organ segmentation. In addition, graphics processing units (GPUs) are utilized as boosters for both real-time Monte Carlo simulations and AI-based image segmentation applications. These advancements provide the feasibility of creating three-dimensional (3D) geometric details of the human anatomy from tomographic imaging and performing Monte Carlo radiation transport simulations using increasingly fast and inexpensive computers. This review first introduces the history of three types of computational human phantoms: stylized medical internal radiation dosimetry (MIRD) phantoms, voxelized tomographic phantoms, and boundary representation (BREP) deformable phantoms. Then, the development of a person-specific phantom is demonstrated by introducing AI-based organ autosegmentation technology. Next, a new development in GPU-based Monte Carlo radiation dose calculations is introduced. Examples of applying computational phantoms and a new Monte Carlo code named ARCHER (Accelerated Radiation-transport Computations in Heterogeneous EnviRonments) to problems in radiation protection, imaging, and radiotherapy are presented from research projects performed by students at the Rensselaer Polytechnic Institute (RPI) and University of Science and Technology of China (USTC). Finally, this review discusses challenges and future research opportunities. We found that, owing to the latest computer hardware and AI technology, computational human body models are moving closer to real human anatomy structures for accurate radiation dose calculations.