Laal M. Innovation process in medical imaging. Proc Soc Behav Sci. 2013;81:60?4. https://doi.org/10.1016/j.sbspro.2013.06.388.
Hussain S, Mubeen I, Ullah N, Shah SSUD, Khan BA, Zahoor M, et al. Modern diagnostic imaging technique applications and risk factors in the medical field: a review. BioMed Res Int. 2022;2022:5164970. https://doi.org/10.1155/2022/5164970.
Morin O, Gillis A, Chen J, Aubin M, Bucci MK, Roach M, et al. Megavoltage cone-beam CT: system description and clinical applications. Med Dosim. 2006;31:51?61. https://doi.org/10.1016/j.meddos.2005.12.009.
Srinivasan K, Mohammadi M, Shepherd J. Applications of linac-mounted kilovoltage cone-beam computed tomography in modern radiation therapy: a review. Pol J Radiol. 2014;79:181?93.
Shakirin G, Braess H, Fiedler F, Kunath D, Laube K, Parodi K, et al. Implementation and workflow for PET monitoring of therapeutic ion irradiation: a comparison of in-beam, in-room, and off-line techniques. Phys Med Biol. 2011;56:1281?98. https://doi.org/10.1088/0031-9155/56/5/004.
Krimmer J, Dauvergne D, Létang JM, Testa É. Prompt-gamma monitoring in hadrontherapy: a review. Nucl Instrum Methods Phys Res Sect A: Accel Spectrometers Detect Assoc Equip. 2018;878:58?73. https://doi.org/10.1016/j.nima.2017.07.063.
Sale KE, JrPM B, Buck RM, Cullen D, Fujino D, Hartmann-Siantar C. Applications of the Monte Carlo radiation transport toolkit at LLNL. Radiat Sources Radiat Interact. 1999. https://doi.org/10.1117/12363708.
Razani A. A Monte Carlo method for radiation transport calculations. J Nucl Sci Technol. 1972;9:551?4. https://doi.org/10.3327/jnst.9.551.
Article MathSciNet Google Scholar
Vassiliev ON. Monte Carlo methods for radiation transport, fundamentals and advanced topics. Biol Med Phys Biomed Eng. 2016. https://doi.org/10.1007/978-3-319-44141-2_7.
Stanley DN, Papanikolaou N, Gutiérrez AN. An evaluation of the stability of image-quality parameters of varian on-board imaging (OBI) and EPID imaging systems. J Appl Clin Méd Phys. 2015;16:87?98. https://doi.org/10.1120/jacmp.v16i2.5088.
Gach HM, Tanase C, Boada F. (2008) 2D & 3D Shepp-Logan Phantom Standards for MRI. In: 2008 19th Int Conf Syst Eng 521?6. https://doi.org/10.1109/icseng.2008.15.
Pan T, Einstein SA, Kappadath SC, Grogg KS, Gomez CL, Alessio AM, et al. Performance evaluation of the 5-ring GE Discovery MI PET/CT system using the national electrical manufacturers association NU 2?2012 Standard. Méd Phys. 2019;46:3025?33. https://doi.org/10.1002/mp.13576.
MacFarlane CR. Radiologists AC of. ACR accreditation of nuclear medicine and PET imaging departments. J Nucl Med Technol. 2006;34:18?24.
Perl J, Shin J, Schümann J, Faddegon B, Paganetti H. TOPAS: an innovative proton Monte Carlo platform for research and clinical applications. Med Phys. 2012;39:6818?37. https://doi.org/10.1118/1.4758060.
Faddegon B, Ramos-Méndez J, Schuemann J, McNamara A, Shin J, Perl J, et al. The TOPAS tool for particle simulation, a Monte Carlo simulation tool for physics, biology and clinical research. Phys Medica. 2020;72:114?21. https://doi.org/10.1016/j.ejmp.2020.03.019.
Lee H, Cheon B-W, Feld JW, Grogg K, Perl J, Ramos-Méndez JA, et al. TOPAS-imaging: extensions to the TOPAS simulation toolkit for medical imaging systems. Phys Med Biol. 2023;68:084001. https://doi.org/10.1088/1361-6560/acc565.
Mainegra-Hing E, Kawrakow I. Variance reduction techniques for fast Monte Carlo CBCT scatter correction calculations. Phys Med Biol. 2010;55:4495?507. https://doi.org/10.1088/0031-9155/55/16/s05.
Staelens S, Beenhouwer JD, Kruecker D, Maigne L, Rannou F, Ferrer L, et al. GATE: Improving the computational efficiency. Nucl Instrum Methods Phys Res Sect A: Accel Spectrometers, Detect Assoc Equip. 2006;569:341?5. https://doi.org/10.1016/j.nima.2006.08.070.
Haynor DR, Harrison RL, Lewellen TK, Bice AN, Anson CP, Gillispie SB, et al. Improving the efficiency of emission tomography simulations using variance reduction techniques. IEEE Trans Nucl Sci. 1990;37:749?53. https://doi.org/10.1109/23.106709.
Shi M, Myronakis M, Hu Y-H, Jacobson M, Lehmann M, Fueglistaller R, et al. A novel method for fast image simulation of flat panel detectors. Phys Med Biology. 2019;64:095019. https://doi.org/10.1088/1361-6560/ab12aa.
Lin EC. Radiation risk from medical imaging. Mayo Clin Proc. 2010;85:1142?6. https://doi.org/10.4065/mcp.2010.0260.
Shope TB, Gagne RM, Johnson GC. A method for describing the doses delivered by transmission X-ray computed tomography. Med Phys. 1981;8:488?95. https://doi.org/10.1118/1.594995.
Treb K, Li K. Accuracy of weighted CTDI in estimating average dose delivered to CTDI phantoms: an experimental study. Méd Phys. 2020;47:6484?99. https://doi.org/10.1002/mp.14528.
Toohey RE, Stabin MG, Watson EE. The AAPM/RSNA physics tutorial for residents. Radiographics. 2000;20:533?46. https://doi.org/10.1148/radiographics.20.2.g00mc33533.
Marin JFG, Nunes RF, Coutinho AM, Zaniboni EC, Costa LB, Barbosa FG, et al. Theranostics in nuclear medicine: emerging and re-emerging integrated imaging and therapies in the era of precision oncology. Radiographics. 2020;40:1715?40. https://doi.org/10.1148/rg.2020200021.
Reinhart AM, Fast MF, Ziegenhein P, Nill S, Oelfke U. A kernel-based dose calculation algorithm for kV photon beams with explicit handling of energy and material dependencies. Br J Radiol. 2016;90:20160426. https://doi.org/10.1259/bjr.20160426.
Heidarloo N, Aghamiri SMR, Saghamanesh S, Azma Z, Alaei P. A novel analytical method for computing dose from kilovoltage beams used in image-guided radiation therapy. Phys Med. 2022;96:54?61. https://doi.org/10.1016/j.ejmp.2022.02.020.
Graves S, Tiwari A, Sunderland J. Collapsed-cone convolution superposition for improved accuracy of voxelwise dosimetry. J Nucl Med. 2020;61:535.
Tian X, Segars WP, Dixon RL, Samei E. Convolution-based estimation of organ dose in tube current modulated CT. Phys Med Biol. 2016;61:3935?54. https://doi.org/10.1088/0031-9155/61/10/3935.
Graves SA, Flynn RT, Hyer DE. Dose point kernels for 2,174 radionuclides. Med Phys. 2019;46:5284?93. https://doi.org/10.1002/mp.13789.
Heidarloo N, Aghamiri SMR, Saghamanesh S, Azma Z, Alaei P. Generation of material-specific energy deposition kernels for kilovoltage X-ray dose calculations. Med Phys. 2021. https://doi.org/10.1002/mp.15061.
Alaei P, Gerbi BJ, Geise RA. Generation and use of photon energy deposition kernels for diagnostic quality X rays. Med Phys. 1999;26:1687?97. https://doi.org/10.1118/1.598674.
Tiwari A, Graves S, Sunderland J. Measurements of dose point kernels using GATE Monte Carlo toolkit for personalized convolution dosimetry. J Nucl Med. 2019;60:274.
Papadimitroulas P. Dosimetry applications in GATE Monte Carlo toolkit. Phys Med. 2017;41:136?40. https://doi.org/10.1016/j.ejmp.2017.02.005.
Huang C-Y, Chu T-C, Lin S-Y, Lin J-P, Hsieh C-Y. Accuracy of the convolution/superposition dose calculation algorithm at the condition of electron disequilibrium. Appl Radiat Isot. 2002;57:825?30. https://doi.org/10.1016/s0969-8043(02)00228-2.
Jacques R, McNutt T. An improved method of heterogeneity compensation for the convolution/superposition algorithm. J Phys Conf Ser. 2014;489:012019. https://doi.org/10.1088/1742-6596/489/1/012019.
Aspradakis MM, Morrison RH, Richmond ND, Steele A. Experimental verification of convolution/superposition photon dose calculations for radiotherapy treatment planning. Phys Med Biol. 2003;48:2873?93. https://doi.org/10.1088/0031-9155/48/17/309.
Bertolet A, Wehrenberg-Klee E, Bobi? M, Grassberger C, Perl J, Paganetti H, et al. Pre- and post-treatment image-based dosimetry in 90Y-microsphere radioembolization using the TOPAS Monte Carlo toolkit. Phys Med Biol. 2021. https://doi.org/10.1088/1361-6560/ac43fd.
Koblinger L, Zarand P. Monte Carlo calculations on chest X-ray examinations for the determination of the absorbed dose and image quality. Phys Med Biol. 1973;18:518?31. https://doi.org/10.1088/0031-9155/18/4/004.
Correa SCA, Souza EM, Silva AX, Lopes RT, Yoriyaz H. Dose?image quality study in digital chest radiography using Monte Carlo simulation. Appl Radiat Isot. 2008;66:1213?7. https://doi.org/10.1016/j.apradiso.2008.01.009.
留言 (0)