Journal of Radiation Protection and Research

The Korean Association for Radiation Protection (대한방사선방어학회)
권호 표지
DOI QR코드

DOI QR Code

A Review of Computational Phantoms for Quality Assurance in Radiology and Radiotherapy in the Deep-Learning Era

  • Peng, Zhao (School of Nuclear Science and Technology, University of Science and Technology of China) ;
  • Gao, Ning (School of Nuclear Science and Technology, University of Science and Technology of China) ;
  • Wu, Bingzhi (School of Nuclear Science and Technology, University of Science and Technology of China) ;
  • Chen, Zhi (School of Nuclear Science and Technology, University of Science and Technology of China) ;
  • Xu, X. George (School of Nuclear Science and Technology, University of Science and Technology of China)
  • Received : 2021.10.30
  • Accepted : 2021.12.20
  • Published : 2022.09.30
Download PDF
⟨ Previous Next ⟩

Abstract

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.

Keywords

Acknowledgement

This work was supported in part by University of Science and Technology of China (USTC) grants on "New Medicine Team Project: The ROADMAP Medical Physics Platform" and "Med-X Medical Physics and Biomedical Engineering Interdisciplinary Subjects" Strategic Priority Research Program (No. XDB39040600), and in part by Natural Science Foundation of Anhui Province, China (No. 1908085MA27).

References

  1. Xu XG. An exponential growth of computational phantom research in radiation protection, imaging, and radiotherapy: a review of the fifty-year history. Phys Med Biol. 2014;59(18):R233-R2302. https://doi.org/10.1088/0031-9155/59/18/R233
  2. Eckerman KF, Poston JW, Bolch WE, Xu XG. Stylized computational phantoms developed at ORNL and elsewhere. In: Handbook of anatomical models for radiation dosimetry. Boca Raton, FL: CRC Press; 2009. p. 43-64.
  3. Agostinelli S, Allison J, Amako KA, Apostolakis J, Araujo H, Arce P, et al. GEANT4-a simulation toolkit. Nucl Instrum Methods Phys Res A. 2003;506(3):250-303. https://doi.org/10.1016/S0168-9002(03)01368-8
  4. Leyton M. A generative theory of shape. Berlin, Germany: Springer; 2001.
  5. Stroud I. Boundary representation modelling techniques. London, UK: Springer; 2006.
  6. Caon M. Voxel-based computational models of real human anatomy: a review. Radiat Environ Biophys. 2004;42(4):229-235. https://doi.org/10.1007/s00411-003-0221-8
  7. Zaidi H, Xu XG. Computational anthropomorphic models of the human anatomy: the path to realistic Monte Carlo modeling in radiological sciences. Annu Rev Biomed Eng. 2007;9:471-500. https://doi.org/10.1146/annurev.bioeng.9.060906.151934
  8. Xu XG, Eckerman KF. Handbook of anatomical models for radiation dosimetry. Boca Raton, FL: CRC Press; 2009.
  9. International Commission on Radiological Protection. Report of Committee II on permissible dose for internal radiation. Oxford, UK: Pergamon; 1959.
  10. Fisher HL, Snyder WS. Variation of dose delivered by 137Cs as a function of body size from infancy to adulthood. Oak Ridge, TN: Oak Ridge National Laboratory; 1966. p. 221-228.
  11. Snyder WS, Fisher HL Jr, Ford MR, Warner GG. Estimates of absorbed fractions for monoenergetic photon sources uniformly distributed in various organs of a heterogeneous phantom. J Nucl Med. 1969:Suppl 3:7-52.
  12. International Commission on Radiological Protection. Report of the Task Group on Reference Man (ICRP Publication 23). Oxford, UK: Pergamon; 1975.
  13. Snyder WS. Estimates of specific absorbed fractions for monoenergetic photon sources uniformly distributed in various organs of a heterogeneous phantom. New York, NY: Society of Nuclear Medicine; 1978.
  14. Hwang JM, Shoup RL, Poston JW. Mathematical description of a newborn human for use in dosimetry calculations. Oak Ridge, TN: Oak Ridge National Laboratory; 1976.
  15. Jones RM, Poston JW, Hwang JL, Jones TD, Warner GG. Development and use of a fifteen year-old equivalent mathematical phantom for internal dose calculations (No. ORNL/TM-5278). Oak Ridge, TN: Oak Ridge National Laboratory; 1976.
  16. Deus SF, Poston JW. Development of a mathematical phantom representing a ten-year-old for use in internal dosimetry calculations. Oak Ridge, TN: Oak Ridge National Laboratory; 1976.
  17. Cristy, M. Mathematical phantoms representing children of various ages for use in estimates of internal dose. Oak Ridge, TN: Oak Ridge National Laboratory; 1980.
  18. Cristy M, Eckerman KF. Specific absorbed fractions of energy at various ages from internal photon sources (1. Methods). Oak Ridge, TN: Oak Ridge National Laboratory; 1987.
  19. Stabin MG, Watson EE, Cristy M, Ryman JC, Eckerman KF, Davis JL, et al. Mathematical models and specific absorbed fractions of photon energy in the nonpregnant adult female and at the end of each trimester of pregnancy. Oak Ridge, TN: Oak Ridge National Laboratory; 1995.
  20. Billings MP, Yucker WR. The computerized anatomical man (CAM) model (No. NASA CR-134043). Washington, DC: Government Printing Office; 1973.
  21. Computational Medical Physics Working Group. Phantoms [Internet]. La Grange Park, IL; American Nuclear Society; c2005 [cited 2022 Jun 1]. Available from: http://cmpwg.ans.org/phantoms.html.
  22. Bouchet LG, Bolch WE, Weber DA, Atkins HL, Poston JW Sr. MIRD Pamphlet No. 15: radionuclide S values in a revised dosimetric model of the adult head and brain: medical internal radiation dose. J Nucl Med. 1999;40(3):62S-101S.
  23. Bouchet LG, Bolch WE, Blanco HP, Wessels BW, Siegel JA, Rajon DA, et al. MIRD Pamphlet No 19: absorbed fractions and radionuclide S values for six age-dependent multiregion models of the kidney. J Nucl Med. 2003;44(7):1113-1147.
  24. Pretorius PH, Xia W, King MA, Tsui BM, Pan TS, Villegas BJ. Evaluation of right and left ventricular volume and ejection fraction using a mathematical cardiac torso phantom. J Nucl Med. 1997;38(10):1528-1535.
  25. Tsui BM, Terry JA, Gullberg GT. Evaluation of cardiac cone-beam single photon emission computed tomography using observer performance experiments and receiver operating characteristic analysis. Invest Radiol. 1993;28(12):1101-1112. https://doi.org/10.1097/00004424-199312000-00004
  26. Tsui BM, Zhao XD, Gregoriou GK, Lalushl DS, Frey EC, Johnston RE, et al. Quantitative cardiac SPECT reconstruction with reduced image degradation due to patient anatomy. IEEE Trans Nucl Sci. 1994;41(6):2838-2844. https://doi.org/10.1109/23.340655
  27. Chen J. Mathematical models of the embryo and fetus for use in radiological protection. Health Phys. 2004;86(3):285-295. https://doi.org/10.1097/00004032-200403000-00005
  28. Park S, Lee JK, Lee C. Development of a Korean adult male computational phantom for internal dosimetry calculation. Radiat Prot Dosimetry. 2006;121(3):257-264. https://doi.org/10.1093/rpd/ncl042
  29. Hegenbart L, Na YH, Zhang JY, Urban M, Xu XG. A Monte Carlo study of lung counting efficiency for female workers of different breast sizes using deformable phantoms. Phys Med Biol. 2008;53(19):5527-5538. https://doi.org/10.1088/0031-9155/53/19/017
  30. Qiu R, Li J, Zhang Z, Wu Z, Zeng Z, Fan J. Photon SAF calculation based on the Chinese mathematical phantom and comparison with the ORNL phantoms. Health Phys. 2008;95(6):716-724. https://doi.org/10.1097/01.HP.0000318889.50519.56
  31. Kim JH, Kim CS, Whang JH. Assessment of radiation dose for surrounding organs and persons approaching implanted patients upon brachytherapy of prostate cancer with Iridium-192. Radiat Prot Dosimetry. 2010;141(3):283-288. https://doi.org/10.1093/rpd/ncq181
  32. Bento J, Barros S, Teles P, Neves M, Goncalves I, Corisco J, et al. Monte Carlo simulation of the movement and detection efficiency of a whole-body counting system using a BOMAB phantom. Radiat Prot Dosimetry. 2012;148(4):403-413. https://doi.org/10.1093/rpd/ncr201
  33. Bhati S, Patni HK, Ghare VP, Singh IS, Nadar MY. Monte Carlo calculations for efficiency calibration of a whole-body monitor using BOMAB phantoms of different sizes. Radiat Prot Dosimetry. 2012;148(4):414-419. https://doi.org/10.1093/rpd/ncr203
  34. Gardumi A, Farah J, Desbree A. Creation of ORNL NURBS-based phantoms: evaluation of the voxel effect on absorbed doses from radiopharmaceuticals. Radiat Prot Dosimetry. 2013;153(3):273-281. https://doi.org/10.1093/rpd/ncs103
  35. Valentin J. Basic anatomical and physiological data for use in radiological protection: reference values (ICRP Publication 89). Ann ICRP. 2002;32(3-4):5-265. https://doi.org/10.1016/S0146-6453(02)00021-0
  36. International Commission on Radiation Units and Measurements. Phantoms and computational models in therapy, diagnosis and protection. Bethesda, MD: International Commission on Radiation Units and Measurements; 1992.
  37. Gu J, Bednarz B, Xu XG, Jiang SB. Assessment of patient organ doses and effective doses using the VIP-Man adult male phantom for selected cone-beam CT imaging procedures during image guided radiation therapy. Radiat Prot Dosimetry. 2008;131(4):431-443. https://doi.org/10.1093/rpd/ncn200
  38. Stovall M, Smith SA, Rosenstein M. Tissue doses from radiotherapy of cancer of the uterine cervix. Med Phys. 1989;16(5):726-733. https://doi.org/10.1118/1.596331
  39. Reece WD, Poston Sr JW, Xu XG. Determining the effective dose equivalent for external photon radiation: calculational results for beam and point source geometries. Radiat Prot Dosim. 1994;55(1):5-21. https://doi.org/10.1093/oxfordjournals.rpd.a082370
  40. Xu XG, Reece WD, Poston JW Sr. A study of the angular dependence problem in effective dose equivalent assessment. Health Phys. 1995;68(2):214-224. https://doi.org/10.1097/00004032-199502000-00007
  41. Xu XG, Reece WD. Sex-specific tissue weighting factors for effective dose equivalent calculations. Health Phys. 1996;70(1):81-86. https://doi.org/10.1097/00004032-199601000-00012
  42. Reece WD, Xu XG. Determining the effective dose equivalent for external photon radiation: assessing effective dose equivalent from personnel dosemeter readings. Radiat Prot Dosim. 1997;69(3):167-178. https://doi.org/10.1093/oxfordjournals.rpd.a031901
  43. Xu XG, Chao TC, Bozkurt A. VIP-Man: an image-based whole-body adult male model constructed from color photographs of the Visible Human Project for multi-particle Monte Carlo calculations. Health Phys. 2000;78(5):476-486. https://doi.org/10.1097/00004032-200005000-00003
  44. Pujol A Jr, Gibbs SJ. A Monte Carlo method for patient dosimetry from dental X-ray. Dentomaxillofac Radiol. 1982;11(1):25-33. https://doi.org/10.1259/dmfr.1982.0003
  45. Gibbs SJ, Pujol A Jr, Chen TS, Malcolm AW, James AE Jr. Patient risk from interproximal radiography. Oral Surg Oral Med Oral Pathol. 1984;58(3):347-354. https://doi.org/10.1016/0030-4220(84)90066-5
  46. Gibbs SJ, Pujol A Jr, Chen TS, Carlton JC, Dosmann MA, Malcolm AW, et al. Radiation doses to sensitive organs from intraoral dental radiography. Dentomaxillofac Radiol. 1987;16(2):67-77. https://doi.org/10.1259/dmfr.1987.0010
  47. Williams G, Zankl M, Abmayr W, Veit R, Drexler G. The calculation of dose from external photon exposures using reference and realistic human phantoms and Monte Carlo methods. Phys Med Biol. 1986;31(4):449-452. https://doi.org/10.1088/0031-9155/31/4/010
  48. Zankl M, Veit R, Williams G, Schneider K, Fendel H, Petoussi N, et al. The construction of computer tomographic phantoms and their application in radiology and radiation protection. Radiat Environ Biophys. 1988;27(2):153-164. https://doi.org/10.1007/BF01214605
  49. Smith T, Petoussi-Henss N, Zankl M. Comparison of internal radiation doses estimated by MIRD and voxel techniques for a "family" of phantoms. Eur J Nucl Med. 2000;27(9):1387-1398. https://doi.org/10.1007/s002590000294
  50. Zanki M, Fill U, Petoussi-Henss N, Regulla D. Organ dose conversion coefficients for external photon irradiation of male and female voxel models. Phys Med Biol. 2002;47(14):2367-2385. https://doi.org/10.1088/0031-9155/47/14/301
  51. Fill UA, Zankl M, Petoussi-Henss N, Siebert M, Regulla D. Adult female voxel models of different stature and photon conversion coefficients for radiation protection. Health Phys. 2004;86(3):253-272. https://doi.org/10.1097/00004032-200403000-00003
  52. Becker J, Zankl M, Petoussi-Henss N. A software tool for modification of human voxel models used for application in radiation protection. Phys Med Biol. 2007;52(9):N195-N205. https://doi.org/10.1088/0031-9155/52/9/N01
  53. International Commission on Radiological Protection. 2002 Annual report of the International Commission on Radiological Protection [Internet]. Ottawa, Canada: International Commission on Radiological Protection; 2003 [cited 2022 Oct 4]. Available: https://www.icrp.org/docs/2002_ann_rep_52_429_03.pdf.
  54. Schlattl H, Zankl M, Petoussi-Henss N. Organ dose conversion coefficients for voxel models of the reference male and female from idealized photon exposures. Phys Med Biol. 2007;52(8):2123-2145. https://doi.org/10.1088/0031-9155/52/8/006
  55. Menzel HG, Clement C, DeLuca P. Realistic reference phantoms: an ICRP/ICRU joint effort. A report of adult reference computational phantoms (ICRP Publication 110). Ann ICRP. 2009;39(2):1-164. https://doi.org/10.1016/j.icrp.2009.07.001
  56. Zubal IG, Harrell CR, Smith EO, Rattner Z, Gindi G, Hoffer PB. Computerized three-dimensional segmented human anatomy. Med Phys. 1994;21(2):299-302. https://doi.org/10.1118/1.597290
  57. Dawson TW, Caputa K, Stuchly MA. A comparison of 60 Hz uniform magnetic and electric induction in the human body. Phys Med Biol. 1997;42(12):2319-2329. https://doi.org/10.1088/0031-9155/42/12/001
  58. Sjogreen K, Ljungberg M, Wingardh K, Erlandsson K, Strand SE. Registration of emission and transmission whole-body scintillation-camera images. J Nucl Med. 2001;42(10):1563-1570.
  59. Kramer R, Vieira JW, Khoury HJ, Lima FR, Fuelle D. All about MAX: a male adult voxel phantom for Monte Carlo calculations in radiation protection dosimetry. Phys Med Biol. 2003;48(10):1239-1262. https://doi.org/10.1088/0031-9155/48/10/301
  60. Kramer R, Khoury HJ, Vieira JW, Loureiro EC, Lima VJ, Lima FR, et al. All about FAX: a Female Adult voXel phantom for Monte Carlo calculation in radiation protection dosimetry. Phys Med Biol. 2004;49(23):5203-5216. https://doi.org/10.1088/0031-9155/49/23/001
  61. Kramer R, Khoury HJ, Vieira JW, Lima VJ. MAX06 and FAX06: update of two adult human phantoms for radiation protection dosimetry. Phys Med Biol. 2006;51(14):3331-3346. https://doi.org/10.1088/0031-9155/51/14/003
  62. Akkurt H, Bekar KB, Eckerman KF. VOXMAT: phantom model with combination of voxel and mathematical geometry. Health Phys. 2008;95(1):S100.
  63. Dimbylow PJ. The development of realistic voxel phantoms for electromagnetic field dosimetry. Proceedings of an International Workshop on Voxel Phantom Development; 1995 Jul 6-7; Chilton, UK.
  64. Dimbylow PJ. FDTD calculations of the whole-body averaged SAR in an anatomically realistic voxel model of the human body from 1 MHz to 1 GHz. Phys Med Biol. 1997;42(3):479-490. https://doi.org/10.1088/0031-9155/42/3/003
  65. Jones DG. A realistic anthropomorphic phantom for calculating organ doses arising from external photon irradiation. Radiat Prot Dosim. 1997;72(1):21-29. https://doi.org/10.1093/oxfordjournals.rpd.a032072
  66. Dimbylow P. Development of the female voxel phantom, NAOMI, and its application to calculations of induced current densities and electric fields from applied low frequency magnetic and electric fields. Phys Med Biol. 2005;50(6):1047-1070. https://doi.org/10.1088/0031-9155/50/6/002
  67. Ferrari P, Gualdrini G. An improved MCNP version of the NORMAN voxel phantom for dosimetry studies. Phys Med Biol. 2005;50:4299-4316. https://doi.org/10.1088/0031-9155/50/18/005
  68. Dimbylow P. Development of pregnant female, hybrid voxelmathematical models and their application to the dosimetry of applied magnetic and electric fields at 50 Hz. Phys Med Biol. 2006;51(10):2383-2394. https://doi.org/10.1088/0031-9155/51/10/003
  69. Dimbylow P, Bolch W, Lee C. SAR calculations from 20 MHz to 6 GHz in the University of Florida newborn voxel phantom and their implications for dosimetry. Phys Med Biol. 2010;55(5):1519-1530. https://doi.org/10.1088/0031-9155/55/5/017
  70. Caon M, Bibbo G, Pattison J. An EGS4-ready tomographic computational model of a 14-year-old female torso for calculating organ doses from CT examinations. Phys Med Biol. 1999;44(9):2213-2225. https://doi.org/10.1088/0031-9155/44/9/309
  71. Caon M, Bibbo G, Pattison J. Monte Carlo calculated effective dose to teenage girls from computed tomography examinations. Radiat Prot Dosim. 2000;90(4):445-448. https://doi.org/10.1093/oxfordjournals.rpd.a033172
  72. Spitzer VM, Whitlock DG. Atlas of the visible human male: reverse engineering of the human body. Sudbury, MA: Jones & Bartlett Learning. 1998.
  73. Shi C, Xu XG. Development of a 30-week-pregnant female tomographic model from computed tomography (CT) images for Monte Carlo organ dose calculations. Med Phys. 2004;31(9):2491-2497. https://doi.org/10.1118/1.1778836
  74. Shi CY, Xu XG, Stabin MG. SAF values for internal photon emitters calculated for the RPI-P pregnant-female models using Monte Carlo methods. Med Phys. 2008;35(7):3215-3224. https://doi.org/10.1118/1.2936414
  75. Nipper JC, Williams JL, Bolch WE. Creation of two tomographic voxel models of paediatric patients in the first year of life. Phys Med Biol. 2002;47(17):3143-3164. https://doi.org/10.1088/0031-9155/47/17/307
  76. Lee C, Williams JL, Lee C, Bolch WE. The UF series of tomographic computational phantoms of pediatric patients. Med Phys. 2005;32(12):3537-3548. https://doi.org/10.1118/1.2107067
  77. Lee C, Lee C, Williams JL, Bolch WE. Whole-body voxel phantoms of paediatric patients: UF Series B. Phys Med Biol. 2006;51(18):4649-4661. https://doi.org/10.1088/0031-9155/51/18/013
  78. Saito K, Wittmann A, Koga S, Ida Y, Kamei T, Funabiki J, et al. Construction of a computed tomographic phantom for a Japanese male adult and dose calculation system. Radiat Environ Biophys. 2001;40(1):69-75. https://doi.org/10.1007/s004110000082
  79. Sato K, Noguchi H, Emoto Y, Koga S, Saito K. Japanese adult male voxel phantom constructed on the basis of CT images. Radiat Prot Dosimetry. 2007;123(3):337-344. https://doi.org/10.1093/rpd/ncl101
  80. Sato K, Noguchi H, Endo A, Emoto Y, Koga S, Saito K. Development of a voxel phantom of Japanese adult male in upright posture. Radiat Prot Dosimetry. 2007;127(1-4):205-208. https://doi.org/10.1093/rpd/ncm272
  81. Takahashi M, Kinase S, Kramer R. Evaluation of counting efficiencies of a whole-body counter using Monte Carlo simulation with voxel phantoms. Radiat Prot Dosimetry. 2011;144(1-4):407-410. https://doi.org/10.1093/rpd/ncq417
  82. Saito K, Koga S, Ida Y, Kamei T, Funabiki J. Construction of a voxel phantom based on CT data for a Japanese female adult and its use for calculation of organ doses from external electrons. Jpn J Health Phys. 2008;43(2):122-130. https://doi.org/10.5453/jhps.43.122
  83. Nagaoka T, Watanabe S, Sakurai K, Kunieda E, Watanabe S, Taki M, et al. Development of realistic high-resolution wholebody voxel models of Japanese adult males and females of average height and weight, and application of models to radiofrequency electromagnetic-field dosimetry. Phys Med Biol. 2004;49(1):1-15. https://doi.org/10.1088/0031-9155/49/1/001
  84. Nagaoka T, Kunieda E, Watanabe S. Proportion-corrected scaled voxel models for Japanese children and their application to the numerical dosimetry of specific absorption rate for frequencies from 30 MHz to 3 GHz. Phys Med Biol. 2008;53(23):6695-6711. https://doi.org/10.1088/0031-9155/53/23/004
  85. Kim CH, Choi SH, Jeong JH, Lee C, Chung MS. HDRK-Man: a whole-body voxel model based on high-resolution color slice images of a Korean adult male cadaver. Phys Med Biol. 2008;53(15):4093-4106. https://doi.org/10.1088/0031-9155/53/15/006
  86. Kim JS, Ha WH, Jeong JH, Cho KW, Lee JK. Use of photographic images to construct voxel phantoms for use in whole-body counting. Radiat Prot Dosimetry. 2010;138(2):119-122. https://doi.org/10.1093/rpd/ncp215
  87. Lee B, Shin G, Kang S, Shin B, Back I, Park H, et al. Dose evaluation of selective collimation effect in cephalography by measurement and Monte Carlo simulation. Radiat Prot Dosimetry. 2012;148(1):58-64. https://doi.org/10.1093/rpd/ncq596
  88. Zhang B, Ma J, Liu L, Cheng J. CNMAN: a Chinese adult male voxel phantom constructed from color photographs of a visible anatomical data set. Radiat Prot Dosimetry. 2007;124(2):130-136. https://doi.org/10.1093/rpd/ncm184
  89. Zhang G, Liu Q, Luo Q. Monte Carlo simulations for external neutron dosimetry based on the visible Chinese human phantom. Phys Med Biol. 2007;52(24):7367-7383. https://doi.org/10.1088/0031-9155/52/24/011
  90. Zhang G, Liu Q, Zeng S, Luo Q. Organ dose calculations by Monte Carlo modeling of the updated VCH adult male phantom against idealized external proton exposure. Phys Med Biol. 2008;53(14):3697-3722. https://doi.org/10.1088/0031-9155/53/14/001
  91. Zhang G, Luo Q, Zeng S, Liu Q. The development and application of the visible Chinese human model for Monte Carlo dose calculations. Health Phys. 2008;94(2):118-125. https://doi.org/10.1097/01.HP.0000285256.48498.b4
  92. Zeng Z, Li J, Qiu R, Jia X. Dose assessment for space radiation using a proton differential dose spectrum. J Tsinghua Univ (Sci Technol) 2006;46(3):374-376. https://doi.org/10.3321/j.issn:1000-0054.2006.03.017
  93. Li J, Qiu R, Zhang Z, Liu L, Zeng Z, Bi L, et al. Organ dose conversion coefficients for external photon irradiation using the Chinese voxel phantom (CVP). Radiat Prot Dosimetry. 2009;135(1):33-42. https://doi.org/10.1093/rpd/ncp087
  94. Tung CJ, Tsai SF, Tsai HY, Chen IJ. Determination of voxel phantom for reference Taiwanese adult from CT image analyses. Radiat Prot Dosimetry. 2011;146(1-3):186-190. https://doi.org/10.1093/rpd/ncr144
  95. Ferrari P. Development of an integrated couple of anthropomorphic models for dosimetric studies. Radiat Prot Dosimetry. 2010;142(2-4):191-200. https://doi.org/10.1093/rpd/ncq194
  96. Alziar I, Bonniaud G, Couanet D, Ruaud JB, Vicente C, Giordana G, et al. Individual radiation therapy patient whole-body phantoms for peripheral dose evaluations: method and specific software. Phys Med Biol. 2009;54(17):N375-N383. https://doi.org/10.1088/0031-9155/54/17/N01
  97. Courageot E, Huet C, Clairand I, Bottollier-Depois JF, Gourmelon P. Numerical dosimetric reconstruction of a radiological accident in South America in April 2009. Radiat Prot Dosimetry. 2011;144(1-4):540-542. https://doi.org/10.1093/rpd/ncq338
  98. Beck P, Zechner A, Rollet S, Berger T, Bergmann R, Hajek M, et al. MATSIM: development of a voxel model of the MATROSHKA astronaut dosimetric phantom. IEEE Trans Nucl Sci. 2011;58(4):1921-1926. https://doi.org/10.1109/TNS.2011.2157704
  99. Mofrad FB, Zoroofi RA, Tehrani-Fard AA, Akhlaghpoor S, Hori M, Chen YW, et al. Statistical construction of a Japanese male liver phantom for internal radionuclide dosimetry. Radiat Prot Dosimetry. 2010;141(2):140-148. https://doi.org/10.1093/rpd/ncq164
  100. Patni HK, Nadar MY, Akar DK, Bhati S, Sarkar PK. Selected organ dose conversion coefficients for external photons calculated using ICRP adult voxel phantoms and Monte Carlo code FLUKA. Radiat Prot Dosimetry. 2011;147(3):406-416. https://doi.org/10.1093/rpd/ncq462
  101. Segars WP. Development and application of the new dynamic NURBS-based cardiac-torso (NCAT) phantom [dissertation]. Chapel Hill, NC: The University of North Carolina at Chapel Hill; 2001.
  102. Segars WP, Lalush DS, Frey EC, Manocha D, King MA, Tsui BM. Improved dynamic cardiac phantom based on 4D NURBS and tagged MRI. IEEE Trans Nucl Sci. 2009;56(5):2728-2738. https://doi.org/10.1109/TNS.2009.2016196
  103. Segars WP, Tsui BM, Frey EC, Johnson GA, Berr SS. Development of a 4-D digital mouse phantom for molecular imaging research. Mol Imaging Biol. 2004;6(3):149-159. https://doi.org/10.1016/j.mibio.2004.03.002
  104. Segars W, Tsui B. 4D MOBY and NCAT phantoms for medical imaging simulation of mice and men. J Nucl Med. 2007;48(suppl 2):203P.
  105. Segars WP, Bond J, Frush J, Hon S, Eckersley C, Williams CH, et al. Population of anatomically variable 4D XCAT adult phantoms for imaging research and optimization. Med Phys. 2013;40(4):043701. https://doi.org/10.1118/1.4794178
  106. Zhang J, Xu GX, Shi C, Fuss M. Development of a geometrybased respiratory motion-simulating patient model for radiation treatment dosimetry. J Appl Clin Med Phys. 2008;9(1):2700.
  107. Tabary J, Marache-Francisco S, Valette S, Segars WP, Lartizien C. Realistic X-Ray CT simulation of the XCAT phantom with SINDBAD. Proceedings of 2009 IEEE Nuclear Science Symposium Conference Record (NSS/MIC); 2009 Oct 24-Nov 1; Orlando, FL. p. 3980-3983.
  108. McGurk R, Seco J, Riboldi M, Wolfgang J, Segars P, Paganetti H. Extension of the NCAT phantom for the investigation of intrafraction respiratory motion in IMRT using 4D Monte Carlo. Phys Med Biol. 2010;55(5):1475-1490. https://doi.org/10.1088/0031-9155/55/5/014
  109. Niu X, Yang Y, Jin M, Wernick MN, King MA. Regularized fully 5D reconstruction of cardiac gated dynamic SPECT images. IEEE Trans Nucl Sci. 2010;57(6):1085-1095. https://doi.org/10.1109/TNS.2010.2047731
  110. Tward DJ, Ceritoglu C, Sturgeon G, Segars WP, Miller MI, Ratnanather JT. Generating patient-specific dosimetry phantoms with whole-body diffeomorphic image registration. Proceedings of 2011 IEEE 37th Annual Northeast Bioengineering Conference (NEBEC); 2011 Apr 1-3; Troy, NY. p. 1-2.
  111. Veress AI, Segars WP, Tsui BM, Gullberg GT. Incorporation of a left ventricle finite element model defining infarction into the XCAT imaging phantom. IEEE Trans Med Imaging. 2011;30(4):915-927. https://doi.org/10.1109/TMI.2010.2089801
  112. Mishra P, Li R, James SS, Mak RH, Williams CL, Yue Y, et al. Evaluation of 3D fluoroscopic image generation from a single planar treatment image on patient data with a modified XCAT phantom. Phys Med Biol. 2013;58(4):841-858. https://doi.org/10.1088/0031-9155/58/4/841
  113. Xu XG, Taranenko V, Zhang J, Shi C. A boundary-representation method for designing whole-body radiation dosimetry models: pregnant females at the ends of three gestational periods: RPI-P3, -P6 and -P9. Phys Med Biol. 2007;52(23):7023-7044. https://doi.org/10.1088/0031-9155/52/23/017
  114. Zhang J, Na YH, Caracappa PF, Xu XG. RPI-AM and RPI-AF, a pair of mesh-based, size-adjustable adult male and female computational phantoms using ICRP-89 parameters and their calculations for organ doses from monoenergetic photon beams. Phys Med Biol. 2009;54(19):5885-5908. https://doi.org/10.1088/0031-9155/54/19/015
  115. Ding A, Mille MM, Liu T, Caracappa PF, Xu XG. Extension of RPI-adult male and female computational phantoms to obese patients and a Monte Carlo study of the effect on CT imaging dose. Phys Med Biol. 2012;57(9):2441-2459. https://doi.org/10.1088/0031-9155/57/9/2441
  116. Han B, Zhang J, Na YH, Caracappa PF, Xu XG. Modelling and Monte Carlo organ dose calculations for workers walking on ground contaminated with Cs-137 and Co-60 gamma sources. Radiat Prot Dosimetry. 2010;141(3):299-304. https://doi.org/10.1093/rpd/ncq184
  117. Su L, Han B, Xu XG. Calculated organ equivalent doses for individuals in a sitting posture above a contaminated ground and a PET imaging room. Radiat Prot Dosimetry. 2012;148(4):439-443. https://doi.org/10.1093/rpd/ncr194
  118. Vazquez JA, Ding A, Haley T, Caracappa PF, Xu XG. A dose-reconstruction study of the 1997 Sarov criticality accident using animated dosimetry techniques. Health Phys. 2014;106(5):571-582. https://doi.org/10.1097/hp.0000000000000019
  119. Lee C, Lodwick D, Hasenauer D, Williams JL, Lee C, Bolch WE. Hybrid computational phantoms of the male and female newborn patient: NURBS-based whole-body models. Phys Med Biol. 2007;52(12):3309-3333. https://doi.org/10.1088/0031-9155/52/12/001
  120. Lee C, Lodwick D, Hurtado J, Pafundi D, Williams JL, Bolch WE. The UF family of reference hybrid phantoms for computational radiation dosimetry. Phys Med Biol. 2010;55(2):339-363. https://doi.org/10.1088/0031-9155/55/2/002
  121. Geyer AM, O'Reilly S, Lee C, Long DJ, Bolch WE. The UF/NCI family of hybrid computational phantoms representing the current US population of male and female children, adolescents, and adults: application to CT dosimetry. Phys Med Biol. 2014;59(18):5225-5242. https://doi.org/10.1088/0031-9155/59/18/5225
  122. Lee C, Lodwick D, Williams JL, Bolch WE. Hybrid computational phantoms of the 15-year male and female adolescent: applications to CT organ dosimetry for patients of variable morphometry. Med Phys. 2008;35(6):2366-2382. https://doi.org/10.1118/1.2912178
  123. Maynard MR, Geyer JW, Aris JP, Shifrin RY, Bolch W. The UF family of hybrid phantoms of the developing human fetus for computational radiation dosimetry. Phys Med Biol. 2011;56(15):4839-4879. https://doi.org/10.1088/0031-9155/56/15/014
  124. Eckerman KF. Aspects of the dosimetry of radionuclides within the skeleton with particular emphasis on the active marrow. Oak Ridge, TN: Oak Ridge National Laboratory; 1985.
  125. Johnson PB, Bahadori AA, Eckerman KF, Lee C, Bolch WE. Response functions for computing absorbed dose to skeletal tissues from photon irradiation: an update. Phys Med Biol. 2011;56(8):2347-2365. https://doi.org/10.1088/0031-9155/56/8/002
  126. Bahadori AA, Johnson P, Jokisch DW, Eckerman KF, Bolch WE. Response functions for computing absorbed dose to skeletal tissues from neutron irradiation. Phys Med Biol. 2011;56(21):6873-6897. https://doi.org/10.1088/0031-9155/56/21/008
  127. Johnson P, Lee C, Johnson K, Siragusa D, Bolch WE. The influence of patient size on dose conversion coefficients: a hybrid phantom study for adult cardiac catheterization. Phys Med Biol. 2009;54(12):3613-3629. https://doi.org/10.1088/0031-9155/54/12/001
  128. Pafundi D, Lee C, Watchman C, Bourke V, Aris J, Shagina N, et al. An image-based skeletal tissue model for the ICRP reference newborn. Phys Med Biol. 2009;54(14):4497-4531. https://doi.org/10.1088/0031-9155/54/14/009
  129. Pafundi D, Rajon D, Jokisch D, Lee C, Bolch W. An imagebased skeletal dosimetry model for the ICRP reference newborn--internal electron sources. Phys Med Biol. 2010;55(7):1785-1814. https://doi.org/10.1088/0031-9155/55/7/002
  130. Hough M, Johnson P, Rajon D, Jokisch D, Lee C, Bolch W. An image-based skeletal dosimetry model for the ICRP reference adult male: internal electron sources. Phys Med Biol. 2011;56(8):2309-2346. https://doi.org/10.1088/0031-9155/56/8/001
  131. Xie T, Bolch WE, Lee C, Zaidi H. Pediatric radiation dosimetry for positron-emitting radionuclides using anthropomorphic phantoms. Med Phys. 2013;40(10):102502. https://doi.org/10.1118/1.4819939
  132. Xie T, Zaidi H. Evaluation of radiation dose to anthropomorphic paediatric models from positron-emitting labelled tracers. Phys Med Biol. 2014;59(5):1165-1187. https://doi.org/10.1088/0031-9155/59/5/1165
  133. Stabin MG, Xu XG, Emmons MA, Segars WP, Shi C, Fernald MJ. RADAR reference adult, pediatric, and pregnant female phantom series for internal and external dosimetry. J Nucl Med. 2012;53(11):1807-1813. https://doi.org/10.2967/jnumed.112.106138
  134. Stabin M, Emmons MA, Segars WP, Fernald M, Brill AB. ICRP89 based adult and pediatric phantom series. J Nucl Med. 2008;49(Suppl 1):14P.
  135. Kramer R, Cassola VF, Khoury HJ, Vieira JW, Lima VJ, Brown KR. FASH and MASH: female and male adult human phantoms based on polygon mesh surfaces: II. Dosimetric calculations. Phys Med Biol. 2010;55(1):163-189. https://doi.org/10.1088/0031-9155/55/1/010
  136. Lima VJ, Cassola VF, Kramer R, Lira CA, Khoury HJ, Vieira JW. Development of 5- and 10-year-old pediatric phantoms based on polygon mesh surfaces. Med Phys. 2011;38(8):4723-4736. https://doi.org/10.1118/1.3615623
  137. Farah J, Broggio D, Franck D. Creation and use of adjustable 3D phantoms: application for the lung monitoring of female workers. Health Phys. 2010;99(5):649-661. https://doi.org/10.1097/HP.0b013e3181dc4f58
  138. Broggio D, Beurrier J, Bremaud M, Desbree A, Farah J, Huet C, et al. Construction of an extended library of adult male 3D models: rationale and results. Phys Med Biol. 2011;56(23):7659-7662. https://doi.org/10.1088/0031-9155/56/23/020
  139. Christ A, Kainz W, Hahn EG, Honegger K, Zefferer M, Neufeld E, et al. The Virtual Family: development of surface-based anatomical models of two adults and two children for dosimetric simulations. Phys Med Biol. 2010;55(2):N23-N38. https://doi.org/10.1088/0031-9155/55/2/N01
  140. Gosselin MC, Neufeld E, Moser H, Huber E, Farcito S, Gerber L, et al. Development of a new generation of high-resolution anatomical models for medical device evaluation: the Virtual Population 3.0. Phys Med Biol. 2014;59(18):5287-5303. https://doi.org/10.1088/0031-9155/59/18/5287
  141. Wu D, Shamsi S, Chen J, Kainz W. Evaluations of specific absorption rate and temperature increase within pregnant female models in magnetic resonance imaging birdcage coils. IEEE Trans Microw Theory Tech. 2006;54(12):4472-4478. https://doi.org/10.1109/TMTT.2006.884655
  142. Gu S, Gupta R, Kyprianou I. Computational high-resolution heart phantoms for medical imaging and dosimetry simulations. Phys Med Biol. 2011;56(18):5845-5864. https://doi.org/10.1088/0031-9155/56/18/005
  143. Kim CH, Jeong JH, Bolch WE, Cho KW, Hwang SB. A polygonsurface reference Korean male phantom (PSRK-Man) and its direct implementation in Geant4 Monte Carlo simulation. Phys Med Biol. 2011;56(10):3137-3161. https://doi.org/10.1088/0031-9155/56/10/016
  144. Han MC, Kim CH, Jeong JH, Yeom YS, Kim S, Wilson PP, et al. DagSolid: a new Geant4 solid class for fast simulation in polygon-mesh geometry. Phys Med Biol. 2013;58(13):4595-4609. https://doi.org/10.1088/0031-9155/58/13/4595
  145. Kainz W, Neufeld E, Bolch WE, Graff CG, Kim CH, Kuster N, et al. Advances in computational human phantoms and their applications in biomedical engineering: a topical review. IEEE Trans Radiat Plasma Med Sci. 2019;3(1):1-23. https://doi.org/10.1109/trpms.2018.2883437
  146. Xu XG, Liu T, Su L, Du X, Riblett M, Ji W, et al. ARCHER, a new Monte Carlo software tool for emerging heterogeneous computing environments. Proceedings of 2013 Joint International Conference on Supercomputing in Nuclear Applications+ Monte Carlo (SNA+MC); 2013 Oct 27-31; Paris, France.
  147. Yeom YS, Jeong JH, Han MC, Kim CH. Tetrahedral-meshbased computational human phantom for fast Monte Carlo dose calculations. Phys Med Biol. 2014;59(12):3173-3185. https://doi.org/10.1088/0031-9155/59/12/3173
  148. Kim CH, Yeom YS, Nguyen TT, Han MC, Choi C, Lee H, et al. New mesh-type phantoms and their dosimetric applications, including emergencies. Ann ICRP. 2018;47(3-4):45-62. https://doi.org/10.1177/0146645318756231
  149. Kim CH, Yeom YS, Petoussi-Henss N, Zankl M, Bolch WE, Lee C, et al. ICRP Publication 145: adult mesh-type reference computational phantoms. Ann ICRP. 2020;49(3):13-201. https://doi.org/10.1177/0146645319893605
  150. Lee H, Yeom YS, Nguyen TT, Choi C, Han H, Shin B, et al. Percentile-specific computational phantoms constructed from ICRP mesh-type reference computational phantoms (MRCPs). Phys Med Biol. 2019;64(4):045005. https://doi.org/10.1088/1361-6560/aafcdb
  151. Choi C, Yeom YS, Lee H, Han H, Shin B, Nguyen TT, et al. Bodysize-dependent phantom library constructed from ICRP meshtype reference computational phantoms. Phys Med Biol. 2020;65(12):125014. https://doi.org/10.1088/1361-6560/ab8ddc
  152. Yeom YS, Han H, Choi C, Nguyen TT, Shin B, Lee C, et al. Posture-dependent dose coefficients of mesh-type ICRP reference computational phantoms for photon external exposures. Phys Med Biol. 2019;64(7):075018. https://doi.org/10.1088/1361-6560/ab0917
  153. Choi C, Shin B, Yeom YS, Nguyen TT, Han H, Ha S, et al. Development of paediatric mesh-type reference computational phantom series of International Commission on Radiological Protection. J Radiol Prot. 2021;41(3):S160. https://doi.org/10.1088/1361-6498/ac0801
  154. Peng Z, Fang X, Yan P, Shan H, Liu T, Pei X, et al. A method of rapid quantification of patient-specific organ doses for CT using deep-learning-based multi-organ segmentation and GPUaccelerated Monte Carlo dose computing. Med Phys. 2020;47(6):2526-2536. https://doi.org/10.1002/mp.14131
  155. Lee C, Liu J, Griffin K, Folio L, Summers RM. Adult patientspecific CT organ dose estimations using automated segmentations and Monte Carlo simulations. Biomed Phys Eng Express. 2020;6(4):045016. https://doi.org/10.1088/2057-1976/ab98e6
  156. Stapleford LJ, Lawson JD, Perkins C, Edelman S, Davis L, McDonald MW, et al. Evaluation of automatic atlas-based lymph node segmentation for head-and-neck cancer. Int J Radiat Oncol Biol Phys. 2010;77(3):959-966. https://doi.org/10.1016/j.ijrobp.2009.09.023
  157. Weszka JS. A survey of threshold selection techniques. Comput Graph Image Process. 1978;7(2):259-265. https://doi.org/10.1016/0146-664X(78)90116-8
  158. Stawiaski J, Decenciere E, Bidault F. Spatio-temporal segmentation for radiotherapy planning. In: Fitt A, Norbury J, Ockendon H, Wilson E, editors. Progress in industrial mathematics at ECMI 2008. Heidelberg, Germany: Springer; 2010. p. 223-228.
  159. Moussallem M, Valette PJ, Traverse-Glehen A, Houzard C, Jegou C, Giammarile F. New strategy for automatic tumor segmentation by adaptive thresholding on PET/CT images. J Appl Clin Med Phys. 2012;13(5):3875.
  160. Boykov YY, Jolly MP. Interactive graph cuts for optimal boundary & region segmentation of objects in ND images. Proceedings of the 8th IEEE International Conference on Computer Vision (ICCV); 2001 Jul 7-14; Vancouver, Canada. p. 105-112.
  161. Mangan AP, Whitaker RT. Partitioning 3D surface meshes using watershed segmentation. IEEE Trans Vis Comput Graph. 1999;5(4):308-321. https://doi.org/10.1109/2945.817348
  162. Kass M, Witkin A, Terzopoulos D. Snakes: active contour models. Int J Comput Vis. 1988;1(4):321-331. https://doi.org/10.1007/BF00133570
  163. El Naqa I, Yang D, Apte A, Khullar D, Mutic S, Zheng J, et al. Concurrent multimodality image segmentation by active contours for radiotherapy treatment planning. Med Phys. 2007;34(12):4738-4749. https://doi.org/10.1118/1.2799886
  164. Zhang Y, Brady M, Smith S. Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm. IEEE Trans Med Imaging. 2001;20(1):45-57. https://doi.org/10.1109/42.906424
  165. Yang J, Beadle BM, Garden AS, Schwartz DL, Aristophanous M. A multimodality segmentation framework for automatic target delineation in head and neck radiotherapy. Med Phys. 2015;42(9):5310-5320. https://doi.org/10.1118/1.4928485
  166. Pekar V, Allaire S, Qazi A, Kim JJ, Jaffray DA. Head and neck auto-segmentation challenge: segmentation of the parotid glands. In: Jiang T, Navab N, Pluim JP, Viergever MA, editors. Medical image computing and computer-assisted intervention - MICCAI 2010. Heidelberg, Germany: Springer, 2010. p. 273-280.
  167. Yang J, Veeraraghavan H, Armato SG 3rd, Farahani K, Kirby JS, Kalpathy-Kramer J, et al. Autosegmentation for thoracic radiation treatment planning: a grand challenge at AAPM 2017. Med Phys. 2018;45(10):4568-4581. https://doi.org/10.1002/mp.13141
  168. Raudaschl PF, Zaffino P, Sharp GC, Spadea MF, Chen A, Dawant BM, et al. Evaluation of segmentation methods on head and neck CT: auto-segmentation challenge 2015. Med Phys. 2017;44(5):2020-2036. https://doi.org/10.1002/mp.12197
  169. Cardenas CE, Mohamed AS, Yang J, Gooding M, Veeraraghavan H, Kalpathy-Cramer J, et al. Head and neck cancer patient images for determining auto-segmentation accuracy in T2-weighted magnetic resonance imaging through expert manual segmentations. Med Phys. 2020;47(5):2317-2322. https://doi.org/10.1002/mp.13942
  170. Yang J, Sharp GC, Gooding MJ. Introduction to Auto-Segmentation in Radiation Oncology. In: Auto-segmentation for radiation oncology. Boca Raton, FL: CRC Press; 2021. p. 1-10.
  171. Ronneberger O, Fischer P, Brox T. U-Net: convolutional networks for biomedical image segmentation. In: Navab N, Hornegger J, Wells W, Frangi A, editors. Medical image computing and computer-assisted intervention - MICCAI 2010. Cham, Switzerland: Springer; 2015. p. 234-241.
  172. Hussain Z, Gimenez F, Yi D, Rubin D. Differential data augmentation techniques for medical imaging classification tasks. AMIA Annu Symp Proc. 2018;2017:979-984.
  173. Shin HC, Roth HR, Gao M, Lu L, Xu Z, Nogues I, et al. Deep convolutional neural networks for computer-aided detection: CNN architectures, dataset characteristics and transfer learning. IEEE Trans Med Imaging. 2016;35(5):1285-1298. https://doi.org/10.1109/TMI.2016.2528162
  174. Samarasinghe G, Jameson M, Vinod S, Field M, Dowling J, Sowmya A, et al. Deep learning for segmentation in radiation therapy planning: a review. J Med Imaging Radiat Oncol. 2021;65(5):578-595. https://doi.org/10.1111/1754-9485.13286
  175. Isensee F, Jaeger PF, Kohl SA, Petersen J, Maier-Hein KH. nnUNet: a self-configuring method for deep learning-based biomedical image segmentation. Nat Methods. 2021;18(2):203-211. https://doi.org/10.1038/s41592-020-01008-z
  176. Carter LM, Camilo Ocampo Ramos J, Bolch WE, Lewis JS, Kesner AL. Technical Note: Patient-morphed mesh-type phantoms to support personalized nuclear medicine dosimetry: a proof of concept study. Med Phys. 2021;48(4):2018-2026. https://doi.org/10.1002/mp.14784
  177. Bagheri M, Parach AA, Razavi-Ratki SK, Nafisi-Moghadam R, Jelodari MA. Patient-specific dosimetry for pediatric imaging of 99mTc-dimercaptosuccinic acid with gate Monte Carlo code. Radiat Prot Dosimetry. 2018;178(2):213-222. https://doi.org/10.1093/rpd/ncx101
  178. Fu W, Ria F, Segars WP, Choudhury KR, Wilson JM, Kapadia AJ, et al. Patient-informed organ dose estimation in clinical CT: implementation and effective dose assessment in 1048 clinical patients. AJR Am J Roentgenol. 2021;216(3):824-834. https://doi.org/10.2214/AJR.19.22482
  179. Raeside DE. Monte Carlo principles and applications. Phys Med Biol. 1976;21(2):181-197. https://doi.org/10.1088/0031-9155/21/2/001
  180. Turner JE, Wright HA, Hamm RN. A Monte Carlo primer for health physicists. Health Phys. 1985;48(6):717-733. https://doi.org/10.1097/00004032-198506000-00001
  181. Andreo P. Monte Carlo techniques in medical radiation physics. Phys Med Biol. 1991;36(7):861-920. https://doi.org/10.1088/0031-9155/36/7/001
  182. Zaidi H. Relevance of accurate Monte Carlo modeling in nuclear medical imaging. Med Phys. 1999;26(4):574-608. https://doi.org/10.1118/1.598559
  183. Rogers DW. Fifty years of Monte Carlo simulations for medical physics. Phys Med Biol. 2006;51(13):R287-R301. https://doi.org/10.1088/0031-9155/51/13/R17
  184. Zaidi H, Sgouros G. Therapeutic applications of Monte Carlo calculations in nuclear medicine. Boca Raton, FL: CRC Press; 2002.
  185. National Research Council Canada. EGSnrc [Internet]. Ottawa, Canada: National Research Council Canada; c2019 [cited 2022 Jun 1]. Available from: https://nrc-cnrc.github.io/EGSnrc/.
  186. Battistoni G, Cerutti F, Fasso A, Ferrari A, Muraro S, Ranft J, et al. The FLUKA code: description and benchmarking. AIP Conf Proc. 2007;896(1):31-49.
  187. Allison J, Amako K, Apostolakis JE, Araujo HA, Dubois PA, Asai MA, et al. Geant4 developments and applications. IEEE Trans Nucl Sci. 2006;53(1):270-278. https://doi.org/10.1109/TNS.2006.869826
  188. Los Alamos National Laboratory. MCNP5: a general Monte Carlo N-particle transport code [Internet]. Los Alamos, NM: Los Alamos National Laboratory; 2003 [cited 2022 Jun 1]. Available from: https://mcnp.lanl.gov/mcnp5.shtml.
  189. Pelowitz DB. MCNPX user's manual version 2.5.0 (No. LACP-05-0369). Los Alamos, NM: Los Alamos National Laboratory; 2005.
  190. Goorley JT, James MR, Booth TE, Brown FB, Bull JS, Cox LJ, et al. Initial MCNP6 release overview-MCNP6 version 1.0 (No. LA-UR-13-22934) [Internet]. Los Alamos, NM: Los Alamos National Laboratory; 2013 [cited 2022 Jun 1]. Available from: https://www.osti.gov/biblio/1086758-initial-mcnp6-release-overview-mcnp6-version.
  191. Salvat F, Fernandez-Varea JM, Sempau J. PENELOPE-2006: a code system for Monte Carlo simulation of electron and photon transport. Barcelona, Spain: Nuclear Energy Agency, Organization for Economic Co-operation and Development; 2006.
  192. Pratx G, Xing L. GPU computing in medical physics: a review. Med Phys. 2011;38(5):2685-2697. https://doi.org/10.1118/1.3578605
  193. Jia X, Xu XG, Orton CG. Point/counterpoint. GPU technology is the hope for near real-time Monte Carlo dose calculations. Med Phys. 2015;42(4):1474-1476. https://doi.org/10.1118/1.4903901
  194. Badal A, Badano A. Accelerating Monte Carlo simulations of photon transport in a voxelized geometry using a massively parallel graphics processing unit. Med Phys. 2009;36(11):4878-4880. https://doi.org/10.1118/1.3231824
  195. Jia X, Gu X, Graves YJ, Folkerts M, Jiang SB. GPU-based fast Monte Carlo simulation for radiotherapy dose calculation. Phys Med Biol. 2011;56(22):7017-7031. https://doi.org/10.1088/0031-9155/56/22/002
  196. Jia X, Gu X, Sempau J, Choi D, Majumdar A, Jiang SB. Development of a GPU-based Monte Carlo dose calculation code for coupled electron-photon transport. Phys Med Biol. 2010;55(11):3077-3086. https://doi.org/10.1088/0031-9155/55/11/006
  197. Hissoiny S, Ozell B, Bouchard H, Despres P. GPUMCD: a new GPU-oriented Monte Carlo dose calculation platform. Med Phys. 2011;38(2):754-764. https://doi.org/10.1118/1.3539725
  198. Tickner J. Monte Carlo simulation of X-ray and gamma-ray photon transport on a graphics-processing unit. Comput Phys Commun. 2010;181(11):1821-1832. https://doi.org/10.1016/j.cpc.2010.07.001
  199. Jia X, Yan H, Gu X, Jiang SB. Fast Monte Carlo simulation for patient-specific CT/CBCT imaging dose calculation. Phys Med Biol. 2012;57(3):577-590. https://doi.org/10.1088/0031-9155/57/3/577
  200. Liu T. Development of ARCHER-a parallel Monte Carlo radiation transport code-for X-ray CT dose calculations using GPU and coprocessor technologies. Troy, NY: Rensselaer Polytechnic Institute; 2014.
  201. Su L, Yang Y, Bednarz B, Sterpin E, Du X, Liu T, et al. ARCHERRT: a GPU-based and photon-electron coupled Monte Carlo dose computing engine for radiation therapy: software development and application to helical tomotherapy. Med Phys. 2014;41(7):071709. https://doi.org/10.1118/1.4884229
  202. Su L. Development and application of a GPU-based fast electron-photon coupled Monte Carlo code for radiation therapy. Troy, NY: Rensselaer Polytechnic Institute; 2014.
  203. Xu Y. Method of virtual source modeling for external photon radiotherapy and its clinical application in dose checking [dissertation]. Hefei, China: University of Science and Technology of China; 2021.
  204. Cardenas CE, Yang J, Anderson BM, Court LE, Brock KB. Advances in auto-segmentation. Semin Radiat Oncol. 2019;29(3):185-197. https://doi.org/10.1016/j.semradonc.2019.02.001
  205. Kurzweil R. The singularity is near: when humans transcend biology. London, UK: Penguin Books; 2005.
  206. Eom J, Xu XG, De S, Shi C. Predictive modeling of lung motion over the entire respiratory cycle using measured pressure-volume data, 4DCT images, and finite-element analysis. Med Phys. 2010;37(8):4389-4400. https://doi.org/10.1118/1.3455276