1. Su L, Yang YM, Bednarz B, Sterpin E, Du X, Liu T, Ji W, Xu XG. ARCHERRT — A Photon-Electron Coupled Monte Carlo Dose Computing Engine for GPU: Software Development of and Application to Helical Tomotherapy. Med Phys. 41:071709 (2014).
2. Xu XG, Liu T, Su L, Du X, Riblett MJ, Ji W, Gu D, Carothers CD, Shephard MS, Brown FB, Kalra MK, Liu B. ARCHER, a New Monte Carlo Software Tool for Emerging Heterogeneous Computing Environments. Annals of Nuclear Energy 82:2–9 (2015).
3. Liu T, Xu XG, and Carothers CD, Comparison of two accelerators for Monte Carlo radiation transport calculations, NVIDIA Tesla M2090 GPU and Intel Xeon Phi 5110p coprocessor: a case study for x-ray CT imaging dose calculation, Annals of Nuclear Energy, 82:230-239 (2015).
4. Lin H, Liu T, Su L, Bednarz B, Caracappa P, Xu XG. Modeling of Radiotherapy Linac Source Terms Using ARCHER Monte Carlo Code: Performance Comparison for GPU and MIC Parallel Computing Devices. EPJ Web of Conferences. 153:04010 (2017).
5. Liu T, Wolfe N, Lin H, et al. Performance Study of Monte Carlo Codes on Xeon Phi Coprocessors — Testing MCNP 6.1 and Profiling ARCHER Geometry Module on the FS7ONNi Problem. EPJ Web of Conferences. 153:06022 (2017).
6. Xu XG. Innovations in computer technologies have impacted radiation dosimetry through anatomically realistic phantoms and fast Monte-Carlo simulations. Health Phys 116(2):263-275 (2019)
7. Adam DP, Liu T, Caracappa PF, Bednarz BP, Xu XG. New capabilities of the Monte Carlo dose engine ARCHER-RT: Clinical validation of the Varian TrueBeam machine for VMAT external beam radiotherapy. Medical Phys. 47(6):2537-2549 (2020).
8. Peng Z, Lu Y, Xu Y, et al. Development of a GPU-accelerated Monte Carlo dose calculation module for nuclear medicine, ARCHER-NM: demonstration for a PET/CT imaging procedure. Physics in Medicine & Biology. 67(6):06NT02 (2022).
9. Peng Z, Gao N, Wu B, Chen Z, Xu XG. A Review of Computational Phantoms for Quality Assurance in Radiology and Radiotherapy in the Deep-Learning Era, Journal of Radiation Protection and Research, 47(3):111-133 (2022)
10. Xu Y, Zhang K, Liu Z, Liang B, Ma X, Ren W, Men K and Dai J (2022) Treatment plan prescreening for patient-specific quality assurance measurements using independent Monte Carlo dose calculations. Front. Oncol. 12:1051110. doi: 10.3389/fonc. 1051110 (2022)
11. Cheng B, Xu Y, Li S, et al. Development and clinical application of a GPU-based Monte Carlo dose verification module and software for 1.5 T MR-LINAC. Medical Phys 50(5):3172-3183 (2023).
12. Li S, Cheng B, Wang Y, Pei X, Xu XG. A GPU-based fast Monte Carlo code that supports proton transport in magnetic field for radiation therapy. Journal of Applied Clinical Medical Physics. 2024;25(1):e14208.
13. Xu Y, Xia W, Ren W, Ma M, Men K, Dai J. Is it necessary to perform measurement-based patient-specific quality assurance for online adaptive radiotherapy with Elekta Unity MR-Linac? Journal of Applied Clinical Medical Physics. e14175 (Early View 2024).
14. Xu XG “Near real-time Monte Carlo dose computing: ARCHER code and its applications to imaging and therapy”. Invited plenary talk for CIRMS Annual Meeting 2014 (National Institute of Standard and Technology, Gaithersburg, MD, March 11, 2014).
15. Liu T, Wolfe N, Su L, Carothers CD, Bednarz B, Xu XG. “Near real-time GPU and MIC-based Monte Carlo code ARCHER for Phantoms”, Proceedings for the 5th International Workshop on Computational Human Phantoms (CP2015) (Seoul, Korea, July 21, 2015)
16. Xu XG “The ARCHER Monte Carlo Code Involving CPU/GPU/MIC”, Invited talk for “Current Issues in Computational Methods — Roundtable”, American Nuclear Society Winter Meeting 2015 (November 9th, 2015, Marriott Wardman Park, Washington, DC)
17. Xu XG “Real-time Monte Carlo-based Radiation Dose Calculations – A dream or reality? ”Invited presentation for The 2nd International Forum on Radiological Medical Physics (Hefei, China, October 18, 2016).
18. Xu XG “Applications of Dynamic Human Phantoms and Real-time Monte Carlo simulations for radiation Therapy” Invited seminar for Medical Physics Program, Dept of Physics, Wuhan University (Wuhan, China, November 25, 2016)
19. Xu XG, Liu T. “Real-time Monte Carlo simulation methods: concept and feasibility”, Proceedings of American Nuclear Society Radiation Protection and Shielding Division (RPSD 2018) 20th Topical Meeting (Santa Fe, NM, August 26–31, 2018)
20. Xu XG “New opportunities in radiation therapy brought by advanced imaging and real-time Monte carlo dose computing technologies”, Invited talk for The 14th Scientific Conference on Radiological Cancer Therapy, Anhui Provincial Medical Conference/The 2nd Hefei Proton and Heavy Ion International Forum (Hefei, Anhui, November 2, 2018).
21. Xu XG “The impact of phantoms, realtime Monte Carlo simulation, and machine learning on Radiation Dosimetry”, Invited plenary presentation for The 3rd International Conference on Dosimetry and its Applications (ICDA-3) (Lisbon, May 27-31, 2019).
22. Xu XG “Radiation Dosimetry Using Computational Phantoms, Realtime Monte Carlo Simulation, and Machine Learning”, Invited seminar, Stanford University, Dept of Bioengineering / Radiology and Dept of Radiation Oncology (Stanford, December 11, 2019).
23. XU XG “From 3D/4D Human Phantoms and Real-Time Monte Carlo Simulation to Deep Learning: Emerging Applications in Medical Physics and Nuclear Engineering”, Invited plenary presentation for Supercomputing in Nuclear Applications + Monte Carlo (SNA + MC) 2020 (Tokyo, May 18-22, 2020).
24. Xu XG “ARCHER: GPU-accelerated “real-time” Monte Carlo code for medical physics applications”, Invited plenary talk for Supercomputing in Nuclear Applications + Monte Carlo (SNA + MC) 2020 (Tokyo, May 18-22, 2020).
25. Peng Z, Shan H, Liu T, Pei X, Wang G, Xu XG. MCDNet – a denoising convolutional neural network to accelerate Monte Carlo radiation transport simulations: A proof of principle with patient dose from X-ray CT Imaging. IEEE Access V7: 76680 – 76689 (2019).
26. Peng Z， Shan H, Liu T, Pei X, Zhou J, Wang G, Xu XG. Deep learning for accelerating Monte Carlo radiation transport simulation in intensity-modulated radiation therapy. arXiv:1910.07735 (2019).
27. Xu XG. “MCDNet: Deep-learning based Monte Carlo denoising for Speeding up radiation transport simulation in CT imaging and radiation therapy”, Invited plenary talk for Supercomputing in Nuclear Applications + Monte Carlo 2020 (Tokyo, May 18-22, 2020)
28. Peng Z, Ni M, Shan H, Lu Y, Li Y, Zhang Y, Pei X, Chen Z, Xie Q, Wang S, Xu XG. Feasibility evaluation of PET scan-time reduction for diagnosing amyloid-beta levels in Alzheimer's disease patients using a deep-learning-based denoising algorithm. Computers in Biology and Medicine. 138:104919 (2021).
29. Bingzhi WU, A quantitative evaluation method for radiotherapy plans quality and its application in clinical rectal cancer, University of Science and Technology of China (Hefei, China) , 2023.
30. Tao QIU, Construction and application of whole-body organ dose data platform for external photon radiotherapy, University of Science and Technology of China (Hefei, China), 2022.
31. Zengpeng ZHANG, The research of proton pen beam algorithm and its clinical test in DeepPlan system, University of Science and Technology of China (Hefei, China), 2021.
32. Yongheng YAN, IMRT automatic planning study based on three-dimensional predicted dose, University of Science and Technology of China (Hefei, China), 2021.
33. Yin TAO, Feasibility analysis of variable radiobiological effects in proton therapy planning, University of Science and Technology of China (Hefei, China), 2021.
34. Zhenjiong SHEN, Multimodal CT-MRI automatic segmentation of small organs-at-risk of the brain using cascaded 3D U-Net network, University of Science and Technology of China (Hefei, China), 2021.
35. Xiangyin MENG, CT automatic delineation of organs-at-risks in radiotherapy planning based on pseudo MRI images, University of Science and Technology of China (Hefei, China), 2021.
36. Yongzhe LI, Calculation of internal radiation absorbed dose based on GPU fast Monte Carlo method, University of Science and Technology of China (Hefei, China), 2021.
37. Gongsen ZHANG, Applications of augmented reality technology to 3D visualization and collision detection in radiotherapy, University of Science and Technology of China (Hefei, China), 2020.
38. Shijie FANG, Improvement and code testing of radiotherapy CCK photon dose algorithms, University of Science and Technology of China (Hefei, China), 2020.
39. Yuchen SONG, A CT image automatic segmentation method for two organs based on two-stage mixed deep-learning models, University of Science and Technology of China, 2020.
40. Xiangyi WU, Pelvis synthetic-CT image generation method based on CycleGAN unpaired training, University of Science and Technology of China (Hefei, China), 2020.
41. Song YUE, A study on cone beam CT rapid reconstruction method and setup of experimental platform, University of Science and Technology of China (Hefei, China), 2020.
42. Zhuo YAN, Shielding optimization for proton therapy based on Monte Carlo simulation and human phantoms, University of Science and Technology of China (Hefei, China), 2020.
43. Lingtong HOU, Monte Carlo analysis of the effects of bladder filling and the applicator displacement on brachytherapy for cervical cancer, University of Science and Technology of China (Hefei, China), 2018.
44. Shi LI, Comparison of detection sensitivity of MLC errors in RapidArc dose verification with ArcCHECK and EPID, University of Science and Technology of China (Hefei, China), 2018.
45. Yuanyuan LIU, A study on systemic dose distribution in patients with TBI based on Monte Carlo simulation, University of Science and Technology of China (Hefei, China), 2018.
46. Lu YANG, Investigation of the impact of magnetic field on Multi-Particle radiation dose in MRIgRT using Monte Carlo software TOPAS, University of Science and Technology of China (Hefei, China), 2018.
47. Taojun SUN, Monte Carlo and phantom calculation of harmful secondary neutron doses in patient undergoing carbon ion brain tumor radiotherapy, University of Science and Technology of China (Hefei, China), 2018.
48. Mang FENG, Development and application of cloud-based software VirtualDose-IR for evaluating radiation doses of interventional radiology patients, University of Science and Technology of China (Hefei, China), 2017.
49. Yankui CHANG, A method of evaluating treatment plans based on interfractional CBCT images and its application in adaptive radiotherapy of cervical cancer, University of Science and Technology of China (Hefei, China), 2023.
50. Zhao PENG, Study on patient-specific radiation dosimetry methods based on PET/CT multi-organ automatic segmentation and fast Monte Carlo calculation, University of Science and Technology of China (Hefei, China), 2022.
51. Lingli MAO, Research on radiation dosimetry of an MRIgRT system under magnetic field, University of Science and Technology of China (Hefei, China), 2021.
52. Yao XU, Method of virtual source modeling for external photon radiotherapy and its clinical application in dose checking, University of Science and Technology of China (Hefei, China), 2021.
53. Zhi WANG, Comparative study and application of deep learning-based auto-segmentation in cervical cancer radiotherapy, University of Science and Technology of China (Hefei, China), 2021.
54. Yaping QI, Mechanistic modelling of radiobiological effects on DNA scale and clinical application, University of Science and Technology of China (Hefei, China), 2021.
55. Jieping ZHOU, The study of IMRT automatic planning based on the hybrid network of 3D residuals and U-Net, University of Science and Technology of China (Hefei, China), 2020.
56. Yi GUO, Study and application of deep learning based image registration in the DeepPlan treatment planning system, University of Science and Technology of China (Hefei, China), 2020.
57. Hongdong LIU, Study on an independent dose verification method and system for proton therapy based on Monte Carlo algorithms, University of Science and Technology of China (Hefei, China), 2019.
58. Wanli HUO, Study and application of proton dose calculations of pencil-beam algorithms for the DeepPlan treatment planning system, University of Science and Technology of China (Hefei, China), 2019.
59. A SULEIMAN, Monte Carlo study of organ doses and related risks for secondary cancer from radiation treatments of cervical and retinoblastoma patients involving Co-60 source, University of Science and Technology of China (Hefei, China), 2019.
60. Hui LIN, GPU-Based Monte Carlo Source Modeling and Simulation for Radiation Therapy Involving Varian Truebeam Linac, Rensselaer Polytechnic Institute (Troy, New York), 2018.
61. Lian ZHANG, Study and application of the highly stable and fast optimization algorithm for intensity modulated proton therapy, University of Science and Technology of China (Hefei, China), 2018.
62. Yifei PI, Development of computational human phantoms and applications to automated CT image segmentation, University of Science and Technology of China (Hefei, China), 2018.
63. Baohui LIANG, The method of estimation size-specific radiation dose of patient in CT examinations, University of Science and Technology of China (Hefei, China), 2016.
64. Lin SU, Development and Application of a GPU-Based Fast Electron-Photon Coupled Monte Carlo Code for Radiation Therapy, Rensselaer Polytechnic Institute （Troy, New York）, 2014.
65. James Tianyu LIU, Development of ARCHER — a Parallel Monte Carlo Radiation Transport Code — for x-Ray CT Dose Calculations using GPU and Coprocessor Technologies, Rensselaer Polytechnic Institute (Troy, New York), 2014.