**Peer-reviewed journals**

[1] H. Lin, T. Liu, C. Shi, S. Petillion, I. Kindts, C. Weltens, T. Depuydt, Y. Song, Z. Saleh, X. G. Xu, and X. Tang, “Feasibility study of individualized optimal positioning selection for left-sided whole breast radiotherapy: DIBH or prone (submitted),” *Journal of Applied Clinical Medical Physics, *(2017).

[2] T. Liu, N. Wolfe, C. D. Carothers, W. Ji, and X. G. Xu, “Optimizing the Monte Carlo neutron cross-section construction code, XSBench, for MIC and GPU platforms,” *Nuclear Science and Engineering, 185*(1), pp. 232-242, (2017). [download]

[3] T. Liu, X. G. Xu, and C. D. Carothers, “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*, pp. 230-239, (2015). [download]

[4] X. G. Xu, T. Liu, L. Su, X. Du, M. Riblett, W. Ji, D. Gu, C. D. Carothers, M. S. Shephard, F. B. Brown, M. K. Kalra, and B. Liu, “ARCHER, a new Monte Carlo software tool for emerging heterogeneous computing environments,” *Annals of Nuclear Energy, 82*, pp. 2-9, (2015). [download]

[5] L. Su, Y. Yang, B. Bednarz, E. Sterpin, X. Du, T. Liu, W. Ji, and X. G. Xu, “ARCHER-RT, A photon-electron coupled Monte Carlo dose computing engine for GPU: software development and application to helical tomotherapy,” *Medical Physics, 41*(7), p. 071709, (2014). [download]

[6] D. Zhang, A. Padole, X. Li, S. Singh, R. D. A. Khawaja, D. Lira, T. Liu, J. Q. Shi, A. Otrakji, M. K. Kalra, X. G. Xu, and B. Liu, “In vitro dose measurements in a human cadaver with abdomen/pelvis CT scans,” *Medical Physics, 41*(9), p. 091911, (2014). [download]

[7] A. Ding, M. Mille, T. Liu, P. F. Caracappa, and X. G. Xu, “Extension of RPI-adult male and female computational phantoms to obese patients and a Monte Carlo study of the effect on CT imaging dose,” *Physics in Medicine and Biology, 57*(9), pp. 2441-2459, (2012). [download]

**Conference abstracts (oral presentations and posters)**

[1] H. Lin, T. Liu, C. Shi, X. Tang, X. Pei, and X. G. Xu, “Automatic lung cancer detection from CT using a GPU-accelerated deep convolutional neural networks,” *Medical Physics, *(2017).

[2] H. Lin, T. Liu, L. Su, C. Shi, X. Tang, D. Adam, B. Bednarz, and X. G. Xu, “Monte Carlo modeling and simulation of the Varian TrueBeam LINAC using heterogeneous computing,” *Medical Physics, *(2017).

[3] T. Liu, H. Lin, B. Bednarz, C. Shi, X. Tang, and X. G. Xu, “Fast Monte Carlo source modeling and dose calculation for magnetic-resonance imaging-guided radiation therapy (MRIgRT),” presented at the 6th International Workshop on Computational Human Phantoms (CP2017), Annapolis, Maryland, USA, (2017).

[4] T. Liu, H. Lin, L. Yang, H. Liu, Z. Wang, X. Pei, Z. Chen, and X. G. Xu, “Fast dose calculation for magnetic-resonance imaging-guided radiation therapy (MRIgRT) using GPU-based Monte Carlo code ARCHER,” *Medical Physics, *(2017).

[5] L. Mao, T. Liu, Y. Gao, L. T. Dauer, P. F. Caracappa, and X. G. Xu, “A study of eye lens dose of interventional radiologist wearing protective eye glasses using fast Monte Carlo simulation code — ARCHER,” *Health Physics, *(2017).

[6] L. Mao, T. Liu, H. Lin, P. Caracappa, Y. Gao, L. Dauer, and X. G. Xu, “A study of dose to the eye Lens of interventional radiologist using MCNP code and multi resolution phantom coupled with eyeglasses model,” *Medical Physics, *(2017).

[7] L. Mao, T. Liu, H. Lin, P. F. Caracappa, Y. Gao, L. T. Dauer, and X. G. Xu, “Radiologist phantom with a high-resolution eye model for interventional radiology simulation,” presented at the 6th International Workshop on Computational Human Phantoms (CP2017), Annapolis, Maryland, USA, (2017).

[8] X. Tang, H. Lin, T. Liu, C. Shi, S. Petillion, I. Kindts, and X. G. Xu, “Feasibility study of a feature based prediction for optimal position selection for left-sided breast radiotherapy,” *Medical Physics, *(2017).

[9] L. Yang, T. Liu, H. Lin, H. Liu, Z. Wang, X. Pei, Z. Chen, and X. G. Xu, “The dosimetric impact of MRI magnetic field on external-beam therapy using GPU-based rapid Monte Carlo code ARCHER,” in *5th Magnetic Resonance (MR) in Radiation Therapy (RT) symposium 2017*, Sydney, Australia, (2017).

[10] H. Lin, T. Liu, C. Shi, S. Petillion, I. Kindts, X. Tang, and X. G. Xu, “Model based classification for optimal position selection for left-sided breast radiotherapy: free breathing, DIBH, or prone,” *Medical Physics, 43*(6), pp. 3629–3630, (2016).

[11] H. Lin, T. Liu, L. Su, B. Bednarz, P. Caracappa, and X. G. Xu, “Modeling of radiotherapy Linac source terms using ARCHER Monte Carlo code: performance comparison for GPU and MIC parallel computing devices,” in *13th International Conference on Radiation Shielding & 19th Topical Meeting of the Radiation Protection and Shielding Division (ICRS-13 & RPSD 2016)*, France, Paris, (2016).

[12] T. Liu, H. Lin, Y. Gao, P. Caracappa, G. Wang, W. Cong, and X. G. Xu, “Radiation dose simulation for a newly proposed dynamic bowtie filters for CT using fast Monte Carlo methods,” *Medical Physics, 43*(6), p. 3861, (2016).

[13] T. Liu, H. Lin, L. Su, C. Shi, X. Tang, B. Bednarz, and X. G. Xu, “Modeling of radiotherapy Linac source terms using ARCHER Monte Carlo code: performance comparison of GPU and MIC computing accelerators,” *Medical Physics, 43*(6), p. 3732, (2016).

[14] T. Liu, N. Wolfe, H. Lin, K. Zieb, W. Ji, P. Caracappa, C. D. Carothers, and X. G. Xu, “Performance study of Monte Carlo codes on Xeon Phi coprocessors — testing MCNP 6.1 and profiling ARCHER geometry module on the FS7ONNi problem,” in *13th International Conference on Radiation Shielding & 19th Topical Meeting of the Radiation Protection and Shielding Division (ICRS-13 & RPSD 2016)*, France, Paris, (2016).

[15] Y. Gao, H. Lin, T. Liu, X. Li, B. Liu, R. Khawaja, M. Kalra, P. Caracappa, and X. G. Xu, “Simulation study of patient off-centering effect on organ dose in chest CT scan,” *Medical Physics, 42*(6), p. 3544, (2015).

[16] Y. Gao, T. Liu, X. Li, B. Liu, M. Kalra, P. Caracappa, and X. G. Xu, “A preliminary method of risk-informed optimization of tube current modulation for dose reduction in CT,” *Medical Physics, 42*(6), p. 3622, (2015).

[17] H. Lin, Y. Gao, T. Liu, D. Gelblum, A. Ho, S. Powell, X. Tang, and X. G. Xu, “Towards quantitative clinical decision on Deep Inspiration Breath Hold (DIBH) Or prone for left-sided breast irradiation,” *Medical Physics, 42*(6), p. 3529, (2015).

[18] H. Liu, T. Liu, X. G. Xu, J. Wu, and W. Zhuo, “Eye lens dose reduction from CT scan using organ based tube current modulation,” *Medical Physics, 42*(6), p. 3250, (2015).

[19] T. Liu, H. Lin, P. F. Caracappa, and X. G. Xu, “Extension of a GPU/MIC based Monte Carlo Code, ARCHER, to internal radiation dose calculations,” *Health Physics, 109*(S1), p. S56, (2015).

[20] T. Liu, H. Lin, X. G. Xu, and M. Stabin, “Development of a nuclear medicine dosimetry module for the GPU-Based Monte Carlo code ARCHER,” *Medical Physics, 42*(6), p. 3661, (2015).

[21] T. Liu, L. Su, X. Du, H. Lin, K. Zieb, W. Ji, P. Caracappa, and X. G. Xu, “Parallel Monte Carlo methods for heterogeneous hardware computer systems using GPUs and coprocessors: recent development of ARCHER code (invited talk),” in *American Nuclear Society (ANS) Annual Meeting 2015*, San Antonio, TX, USA, (2015).

[22] T. Liu, N. Wolfe, C. D. Carothers, W. Ji, and X. G. Xu, “Status of ARCHER — A Monte Carlo Code for the High-Performance Heterogeneous Platforms Involving GPU and MIC,” in *Joint International Conference on Mathematics and Computation (M&C), Supercomputing in Nuclear Applications (SNA) and the Monte Carlo (MC) Method (M&C+SNA+MC 2015)*, Nashville, TN, USA, (2015).

[23] T. Liu, N. Wolfe, C. D. Carothers, W. Ji, and X. G. Xu, “Optimizing the Monte Carlo neutron cross-section construction code, XSBench, to MIC and GPU platforms,” in *Joint International Conference on Mathematics and Computation (M&C), Supercomputing in Nuclear Applications (SNA) and the Monte Carlo (MC) Method (M&C+SNA+MC 2015)*, Nashville, TN, USA, (2015).

[24] T. Liu, N. Wolfe, C. D. Carothers, and X. G. Xu, “Development of a medical physics Monte Carlo radiation transport code ARCHER,” in *GPU Technology Conference 2015*, San Jose, CA, USA, (2015).

[25] T. Liu, N. Wolfe, L. Su, C. D. Carothers, B. Bednarz, and X. G. Xu, “Near real-time GPU and MIC-based Monte Carlo code ARCHER for radiation dose calculations in voxelized and mesh phantoms,” presented at the 5th International Workshop on Computational Human Phantoms (CP2015), Seoul, Korea, (2015).

[26] N. Wolfe, C. D. Carothers, T. Liu, and X. G. Xu, “Concurrent CPU, GPU and MIC execution algorithms for ARCHER Monte Carlo code involving photon and neutron radiation transport problems,” in *Joint International Conference on Mathematics and Computation (M&C), Supercomputing in Nuclear Applications (SNA) and the Monte Carlo (MC) Method (M&C+SNA+MC 2015)*, Nashville, TN, USA, (2015).

[27] X. Du, T. Liu, L. Su, P. F. Caracappa, and X. G. Xu, “Extension of ARCHER Monte Carlo code to health physics dosimetry and shielding design: preliminary results,” *Health Physics, 107*(S1), p. S38, (2014).

[28] X. Du, T. Liu, L. Su, W. Ji, P. F. Caracappa, and X. G. Xu, “Development of CSG-based radiation shielding module for ARCHER: preliminary results for photons,” in *Radiation Protection and Shielding Division of the American Nuclear Society 2014*, Knoxville, TN, USA, (2014).

[29] W. Huo, T. Liu, L. Su, X. Du, Z. Chen, and X. G. Xu, “Comparisons of dosimetric accuracy and calculation time of ARCHER and MCNP5 codes for the Ir-192 brachytherapy case,” in *Radiation Protection and Shielding Division of the American Nuclear Society 2014*, Knoxville, TN, USA, (2014).

[30] H. Lin, T. Liu, L. Su, X. Du, Y. Gao, P. F. Caracappa, and X. G. Xu, “Formation of computational phantoms from CT numbers for use in the ARCHER Monte Carlo code,” *Health Physics, 107*(S1), p. S98, (2014).

[31] T. Liu, X. Du, L. Su, Y. Gao, W. Ji, D. Zhang, J. Q. Shi, B. Liu, M. K. Kalra, and X. G. Xu, “Monte Carlo CT dose calculation: a comparison between experiment and simulation using ARCHER-CT,” *Medical Physics, 41*(6), p. 424, (2014).

[32] T. Liu, X. Du, L. Su, Y. Gao, W. Ji, D. Zhang, J. Q. Shi, B. Liu, M. K. Kalra, and X. G. Xu, “Testing of ARCHER-CT, a fast Monte Carlo Code for CT dose calculation: experiment versus simulation,” *Transactions of the American Nuclear Society, 110*, p. 481, (2014).

[33] T. Liu, X. Du, L. Su, W. Ji, and X. G. Xu, “Development of ARCHER-CT, a fast Monte Carlo code for patient-specific CT dose calculations using Nvidia GPU and Intel coprocessor technologies,” in *GPU Technology Conference 2014*, San Jose, CA, USA, (2014).

[34] T. Liu, L. Su, X. Du, P. F. Caracappa, and X. G. Xu, “Comparison of accuracy and speed of ARCHER with MCNP for organ dose calculations from external photon beams under standard irradiation geometries,” *Health Physics, 107*(S1), p. S114, (2014).

[35] T. Liu, L. Su, X. Du, H. Lin, K. Zieb, W. Ji, P. Caracappa, and X. G. Xu, “Parallel Monte Carlo methods for heterogeneous hardware computer systems using GPUs and coprocessors: recent development of ARCHER code,” in *Radiation Protection and Shielding Division of the American Nuclear Society 2014*, Knoxville, TN, USA, (2014).

[36] N. Wolfe, T. Liu, C. Carothers, and X. G. Xu, “Heterogeneous concurrent execution of Monte Carlo photon transport on CPU, GPU and MIC,” in *Proceedings of the 4th Workshop on Irregular Applications: Architectures and Algorithms*, (2014), pp. 49-52.

[37] X. Du, T. Liu, W. Ji, X. G. Xu, and F. B. Brown, “Evaluation of vectorized Monte Carlo algorithms on GPUs for a neutron eigenvalue problem,” in *Proceedings of International Conference on Mathematics and Computational Methods Applied to Nuclear Science & Engineering (M&C 2013)*, Sun Valley, Idaho, USA, (2013), pp. 2513-2522.

[38] X. Du, T. Liu, L. Su, M. Riblett, and X. G. Xu, “A hardware accelerator based fast Monte Carlo code for radiation dosimetry: software design and preliminary results,” *Medical Physics, 40*(6), p. 475, (2013).

[39] T. Liu, X. Du, W. Ji, X. G. Xu, and F. B. Brown, “A comparative study of history-based versus vectorized Monte Carlo methods in the GPU/CUDA environment for a simple neutron eigenvalue problem,” in *Joint International Conference on Supercomputing in Nuclear Applications and Monte Carlo (SNA & MC 2013)*, Paris, France, (2013).

[40] T. Liu, X. Du, and X. G. Xu, “Affordable supercomputer-based Monte Carlo CT dose calculations: a hardware comparison between Nvidia M2090 GPU and Intel Xeon Phi 5110p coprocessor,” *Medical Physics, 40*(6), p. 459, (2013).

[41] T. Liu, W. Ji, and X. G. Xu, “Development of GPU-based Monte Carlo code for fast CT imaging dose calculation on CUDA Fermi architecture,” in *International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering (M&C 13)*, Sun Valley, ID, (2013).

[42] T. Liu, X. G. Xu, and C. D. Carothers, “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,” in *Joint International Conference on Supercomputing in Nuclear Applications and Monte Carlo (SNA & MC 2013)*, Paris, France, (2013).

[43] M. J. Riblett, T. Liu, W. Ji, and X. G. Xu, “Use of hardware accelerators for Monte Carlo-based neutron radiation transport: a preliminary study,” *Health Physics, 105*(S1), p. S99, (2013).

[44] L. Su, X. Du, T. Liu, and X. G. Xu, “GPU-accelerated Monte Carlo electron transport methods: development and application for radiation dose calculations using six GPU cards,” in *Joint International Conference on Supercomputing in Nuclear Applications and Monte Carlo (SNA & MC 2013)*, Paris, France, (2013).

[45] L. Su, X. Du, T. Liu, and X. G. Xu, “A fast Monte Carlo electron transport code for dose calculations using the GPU accelerator,” *Health Physics, 105*(S1), p. S41, (2013).

[46] L. Su, X. Du, T. Liu, and X. G. Xu, “Fast Monte Carlo electron-photon transport code using hardware accelerators: preliminary results for brachytherapy and radionuclide therapy cases,” *Medical Physics, 40*(6), p. 397, (2013).

[47] X. G. Xu, T. Liu, L. Su, X. Du, M. Riblett, W. Ji, and F. B. Brown, “An update of ARCHER, a Monte Carlo radiation transport software testbed for emerging hardware such as GPUs,” *Transactions of the American Nuclear Society, 108*, pp. 433-434, (2013).

[48] X. G. Xu, T. Liu, L. Su, X. Du, M. J. Riblett, W. Ji, D. Gu, C. D. Carothers, M. S. Shephard, F. B. Brown, M. K. Kalra, and B. Liu, “ARCHER, a new Monte Carlo software tool for emerging heterogeneous computing environments,” in

[49] D. Zhang, W. Cai, X. Li, T. Liu, and B. Liu, “A comparison of radiation dose to the colon between single-energy and dual-energy CT colonography,” in *Radiological Society of North America 2013, 99th Scientific Assembly and Annual Meeting*, Chicago, IL, USA, (2013).

[50] T. Liu, A. Ding, W. Ji, X. G. Xu, C. D. Carothers, and F. B. Brown, “A Monte Carlo neutron transport code for eigenvalue calculations on a dual-GPU system and CUDA environment,” in *International Topical Meeting on Advances in Reactor Physics (PHYSOR 2012)*, Knoxville, TN, USA, (2012).

[51] T. Liu, A. Ding, and X. G. Xu, “Accelerated Monte Carlo methods for photon dosimetry using a dual-GPU system and CUDA,” *Medical Physics, 39*(6), p. 3818, (2012).

[52] T. Liu, A. Ding, and X. G. Xu, “GPU-based Monte Carlo methods for accelerating radiographic and CT imaging dose calculations: feasibility and scalability,” *Medical Physics, 39*(6), p. 3876, (2012).

[53] T. Liu, L. Su, A. Ding, W. Ji, C. D. Carothers, and X. G. Xu, “GPU/CUDA-ready parallel Monte Carlo codes for reactor analysis and other applications,” *Transactions of the American Nuclear Society, 106*, pp. 378-379, (2012).

[54] L. Su, T. Liu, A. Ding, and X. G. Xu, “A GPU/CUDA based Monte Carlo code for proton transport: preliminary results of proton depth dose in water,” *Medical Physics, 39*(6), p. 3945, 2012 (2012).

[55] L. Su, T. Liu, A. Ding, and X. G. Xu, “GPU/CUDA-based Monte Carlo methods for radiation protection dose calculations involving X-ray and proton sources,” *Health Physics, 103*(S1), p. S78, (2012).

[56] X. G. Xu, L. Su, T. Liu, and A. Ding, “GPU-based Monte Carlo method for medical physics applications: preliminary results for x-ray and proton applications,” in *World Congress on Medical Physics and Biomedical Engineering (WC 2012)*, Beijing, China, (2012).

[57] A. Ding, T. Liu, C. Liang, W. Ji, M. S. Shepard, X. G. Xu, and F. B. Brown, “Evaluation of speedup of Monte Carlo calculations of simple reactor physics problems coded for the GPU/CUDA environment,” in *International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering (M&C 11)*, Rio de Janeiro, Brazil, (2011).

[58] T. Liu, A. Ding, P. F. Caracappa, and X. G. Xu, “Modeling of obese individuals using automatic deformation of mesh-based computational phantoms,” *Health Physics, 101*(S1), p. S34, (2011).

[59] M. Mille, A. Ding, T. Liu, Y. Na, P. F. Caracappa, and X. G. Xu, “The effect of patient obesity on PET/CT imaging dose using a phantom with a body mass index of 45,” *Health Physics, 101 *(S1), p. S31, (2011).

[60] X. G. Xu and T. Liu, “Quantifying uncertainty in radiation protection dosimetry using statistical phantoms,” in *The 3rd International Workshop on Computational Phantoms for Radiation Protection, Imaging and Radiotherapy*, Beijing, China, (2011).

[61] T. Liu, M. Mille, P. F. Caracappa, X. G. Xu, S. Nour, and K. Inn, “A software solution to bioassay detector calibration using a library of virtual phantoms,” *Health Physics, 99*(S1), p. S78, (2010).