Computer method and modeling: Medical biophysics applications in cancer therapy, medical imaging and drug delivery

James C.L. Chow; James C.L. Chow

doi:10.3934/biophy.2021017

AIMS Biophysics

2021, Volume 8, Issue 3: 233-235. doi: 10.3934/biophy.2021017

Previous Article Next Article

Editorial Special Issues

Computer method and modeling: Medical biophysics applications in cancer therapy, medical imaging and drug delivery

James C.L. Chow ^{1,2,3
,
,}

1.
Department of Radiation Oncology, University of Toronto, Toronto, Ontario, Canada
2.
Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
3.
Temerty Centre for AI Research and Education in Medicine, University of Toronto, Toronto, Ontario, Canada

Received: 28 May 2021 Accepted: 28 May 2021 Published: 31 May 2021

Citation: James C.L. Chow. Computer method and modeling: Medical biophysics applications in cancer therapy, medical imaging and drug delivery[J]. AIMS Biophysics, 2021, 8(3): 233-235. doi: 10.3934/biophy.2021017

Related Papers:

References

[1]	Rogers DWO (2006) Fifty years of Monte Carlo simulations for medical physics. Phys Med Biol 51: R287. doi: 10.1088/0031-9155/51/13/R17
[2]	Markel D, Alasti H, Chow JCL (2012) Dosimetric Correction for a 4D-Computed Tomography Dataset using the Free-Form Deformation Algorithm. J Phys: Conf Ser 385: 012001. doi: 10.1088/1742-6596/385/1/012001
[3]	Moore JA, Chow JCL (2021) Recent progress and applications of gold nanotechnology in medical biophysics using artificial intelligence and mathematical modeling. Nano Ex 2: 022001. doi: 10.1088/2632-959X/abddd3
[4]	Chow JCL (2017) Internet-based computer technology on radiotherapy. Rep Pract Oncol Radiother 22: 455-462. doi: 10.1016/j.rpor.2017.08.005
[5]	Siddique S, Chow JCL (2020) Artificial intelligence in radiotherapy. Rep Pract Oncol Radiother 25: 656-666. doi: 10.1016/j.rpor.2020.03.015
[6]	Odle T (2020) The AI era: the role of medical imaging and radiation therapy professionals. Radiol Technol 91: 391-400.
[7]	Siddique S, Chow JCL (2021) Machine learning in healthcare communication. Encyclopedia 1: 220-239. doi: 10.3390/encyclopedia1010021
[8]	Chow JCL (2011) A performance evaluation on Monte Carlo simulation for radiation dosimetry using cell processor. J Comp Meth Sci Eng 11: 1-12.
[9]	Spezi E, Lewis G (2008) An overview of Monte Carlo treatment planning for radiotherapy. Radiat Prot Dosim 131: 123-129. doi: 10.1093/rpd/ncn277
[10]	Killoran JH, Kooy HM, Gladstone DJ, et al. (1997) A numerical simulation of organ motion and daily setup uncertainties: implications for radiation therapy. Int J Radiat Oncol Biol Phys 37: 213-221. doi: 10.1016/S0360-3016(96)00477-4
[11]	Bauza X, Chow JCL (2019) An automated scheduling system for radiotherapy physicist on-call using Monte Carlo simulation. Australas Phys Eng Sci Med 42: 27-32. doi: 10.1007/s13246-018-0705-0
[12]	Mohamed M, Chow JCL (2020) A Comprehensive computer database for medical physics on-call program. J Radiother in Pract 19: 10-14. doi: 10.1017/S1460396919000244
[13]	Chow JCL (2018) Recent progress in Monte Carlo simulation on gold nanoparticle radiosensitization. AIMS Biophys 5: 231-244. doi: 10.3934/biophy.2018.4.231
[14]	He C, Chow JCL (2016) Gold nanoparticle DNA damage in radiotherapy: A Monte Carlo study. AIMS Bioeng 3: 352-361. doi: 10.3934/bioeng.2016.3.352
[15]	Siddique S, Chow JCL (2020) Application of nanomaterials in biomedical imaging and cancer therapy. Nanomaterial 10: 1700. doi: 10.3390/nano10091700
[16]	Mututantri-Bastiyange D, Chow JCL (2020) Imaging dose of cone-beam computed tomography in nanoparticle-enhanced image-guided radiotherapy: A Monte Carlo phantom study. AIMS Bioeng 7: 1-11. doi: 10.3934/bioeng.2020001
[17]	Martelli S, Chow JCL (2020) Dose enhancement for the flattening-filter-free and flattening-filter photon beams in nanoparticle-enhanced radiotherapy: A Monte Carlo phantom study. Nanomaterials 10: 637. doi: 10.3390/nano10040637
[18]	Siddique S, Chow JCL (2020) Gold nanoparticles for drug delivery and cancer therapy. App Sci 10: 3824. doi: 10.3390/app10113824
[19]	Ng F, Jiang R, Chow JCL (2020) Predicting treatment planning evaluation parameter using artificial intelligence and machine learning. IOP SciNotes 1: 014003. doi: 10.1088/2633-1357/ab805d
[20]	Kontaxis C, Bol GH, Lagendijk JJW, et al. (2020) DeepDose: towards a fast dose calculation engine for radiation therapy using deep learning. Phys Med Biol 65: 075013. doi: 10.1088/1361-6560/ab7630

Reader Comments

Your name:*

Email:*
© 2021 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)