**Peer-reviewed journals**

Liu, T., Hong, G., and Cai, W., “A comparative study of effective atomic number calculations for dual‐energy CT,” *Medical Physics, 48*(10), pp. 5908-5923, (2021). [download]

Adam, D. P., Liu, T., Caracappa, P. F., Bednarz, B. P., and Xu, X. G., “New capabilities of the Monte Carlo dose engine ARCHER-RT: clinical validation of the Varian TrueBeam machine for VMAT external beam radiotherapy.,” *Medical Physics, *(2020). [download]

Cai, W., Liu, T., Xue, X., Luo, G., Wang, X., Shen, Y., Fang, Q., Sheng, J., Chen, F., and Liang, T., “CT Quantification and Machine-learning Models for Assessment of Disease Severity and Prognosis of COVID-19 Patients,” *Academic Radiology, *(2020). [download]

Gao, Y., Mahmood, U., Liu, T., Quinn, B., Gollub, M., Xu, X. G., and Dauer, L. T., “Patient-specific organ and effective dose estimates in adult oncologic CT,” *American Journal of Roentgenology, 214*(4), pp. 738-746, (2020). [download]

Peng, Z., Fang, X., Yan, P., Shan, H., Liu, T., Pei, X., Wang, G., Liu, B., Kalra, M. K., and Xu, X. G., “A method of rapid quantification of patient‐specific organ doses for CT using deep‐learning based multi‐organ segmentation and GPU‐accelerated Monte Carlo dose computing,” *Medical Physics, *(2020). [download]

Mao, L., Liu, T., Caracappa, P. F., Lin, H., Gao, Y., Dauer, L. T., and Xu, X. G., “Influences of operator head posture and protective eyewear on eye lens doses in interventional radiology: a Monte Carlo study,” *Medical Physics, 46*(6), pp. 2744-2751, (2019). [download]

Peng, Z., Shan, H., Liu, T., Pei, X., Wang, G., and Xu, X. G., “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, 7*, pp. 76680 – 76689, (2019). [download]

Lin, H., Liu, T., Shi, C., Petillion, S., Kindts, I., Weltens, C., Depuydt, T., Song, Y., Saleh, Z., and Xu, X. G., “Feasibility study of individualized optimal positioning selection for left‐sided whole breast radiotherapy: DIBH or prone,” *Journal of applied clinical medical physics, 19*(2), pp. 218-229, (2018). [download]

Pi, Y., Liu, T., and Xu, X. G., “Development of a set of mesh-based and age-dependent Chinese phantoms and application for CT dose calculations,” *Radiation protection dosimetry, *(2018). [download]

Liu, T., Wolfe, N., Carothers, C. D., Ji, W., and Xu, X. G., “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]

Liu, T., Xu, X. G., and Carothers, C. D., “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]

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

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

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

Ding, A., Mille, M., Liu, T., Caracappa, P. F., and Xu, X. G., “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]

**PhD thesis**

Liu, T., “Development of ARCHER — a parallel Monte Carlo radiation transport code — for x-ray CT dose calculations using GPU and coprocessor technologies,” PhD, Mechanical, Aerospace, and Nuclear Engineering, Rensselaer Polytechnic Institute, Troy, New York, (2014). [download]

**Conference abstracts and full papers**

[1] Cai, W., Liu, T., Luo, G., Xue, X., Wang, X., and Chen, F., “CT Imaging of COVID-19 Pneumonia and Its Impacts on Patient Management,” in *Radiological Society of North America (RSNA) 2020*, Chicago, IL, USA, (2020).

[2] Adam, D., Liu, T., Caracappa, P., Xu, X. G., and Bednarz, B., “Implementation and benchmarking of volumetric modulated Arc therapy (VMAT) modeling in the GPU-based high-performance Monte Carlo code ARCHER (forthcoming),” *Medical Physics, *(2019).

[3] Liu, T., Wolfe, N., Lin, H., Carothers, C. D., and Xu, X. G., “Performance study of atomic tally methods for GPU-accelerated Monte Carlo dose calculation,” in *2019 American Nuclear Society (ANS) Annual Meeting*, Minneapolis, MN, USA, (2019).

[4] Peng, Z., Fang, X., Shan, H., Liu, T., Pei, X., Yan, P., Wang, G., Liu, B., and Xu, X. G., “Multi-organ segmentation of CT images using deep-learning for instant and patient-specific dose reporting (forthcoming),” *Medical Physics, *(2019).

[5] Adam, D., Lin, H., Liu, T., Caracappa, P., Xu, X., and Bednarz, B., “Implementation of heterogeneous computing methods and development of an EGSnrc-based external beam dose engine for validating a GPU-based Monte Carlo code, ARCHER,” *Medical Physics, 45*(6), pp. E444-E445, (2018).

[6] Lin, H., Adam, D. P., Liu, T., Caracappa, P. F., Bednarz, B. P., and Xu, a. X. G., “Development of ARCHER towards clinical use: modeling and simulation of Varian LINAC for radiation therapy dose calculations,” in *20th Topical Meeting of the Radiation Protection and Shielding Division of the American Nuclear Society 2018*, Santa Fe, NM, USA, (2018).

[7] Liu, T., Wolfe, N., Lin, H., Carothers, C. D., and Xu, X. G., “Performance study of atomic tally methods for GPU-accelerated Monte Carlo dose calculation,” in *20th Topical Meeting of the Radiation Protection and Shielding Division of the American Nuclear Society 2018*, Santa Fe, NM, USA, (2018). [download]

[8] Mao, L., Liu, T., Gao, Y., Dauer, L. T., Caracappa, P. F., and Xu, X. G., “Occupational radiation protection of radiologists and technicians performing fluoroscopically-guided interventional procedures – an investigation of posture and movement effects,” *Health Physics, 115*(Supplement 1 1), p. S5, (2018).

[9] Lin, H., Liu, T., Shi, C., Tang, X., Pei, X., and Xu, X. G., “Automatic lung cancer detection from CT using a GPU-accelerated deep convolutional neural networks,” *Medical Physics, 44*(6), p. 3178, (2017).

[10] Lin, H., Liu, T., Su, L., Shi, C., Tang, X., Adam, D., Bednarz, B., and Xu, X. G., “Monte Carlo modeling and simulation of the Varian TrueBeam LINAC using heterogeneous computing,” *Medical Physics, 44*(6), p. 3003, (2017).

[11] Liu, T., Lin, H., Bednarz, B., Shi, C., Tang, X., and Xu, X. G., “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).

[12] Liu, T., Lin, H., Yang, L., Liu, H., Wang, Z., Pei, X., Chen, Z., and Xu, X. G., “Fast dose calculation for magnetic-resonance imaging-guided radiation therapy (MRIgRT) using GPU-based Monte Carlo code ARCHER,” *Medical Physics, 44*(6), p. 3131, (2017).

[13] Mao, L., Liu, T., Gao, Y., Dauer, L. T., Caracappa, P. F., and Xu, X. G., “A study of eye lens dose of interventional radiologist wearing protective eye glasses using fast Monte Carlo simulation code — ARCHER,” *Health Physics, 113*(Supplement 1 1), p. S83, (2017).

[14] Mao, L., Liu, T., Lin, H., Caracappa, P., Gao, Y., Dauer, L., and Xu, X. G., “A study of dose to the eye Lens of interventional radiologist using MCNP code and multi resolution phantom coupled with eyeglasses model,” *Medical Physics, 44*(6), p. 3120, (2017).

[15] Mao, L., Liu, T., Lin, H., Caracappa, P. F., Gao, Y., Dauer, L. T., and Xu, X. G., “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).

[16] Tang, X., Lin, H., Liu, T., Shi, C., Petillion, S., Kindts, I., and Xu, X. G., “Feasibility study of a feature based prediction for optimal position selection for left-sided breast radiotherapy,” *Medical Physics, 44*(6), p. 3039, (2017).

[17] Yang, L., Liu, T., Lin, H., Liu, H., Wang, Z., Pei, X., Chen, Z., and Xu, X. G., “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).

[18] Lin, H., Liu, T., Shi, C., Petillion, S., Kindts, I., Tang, X., and Xu, X. G., “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).

[19] Lin, H., Liu, T., Su, L., Bednarz, B., Caracappa, P., and Xu, X. G., “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).

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

[21] Liu, T., Lin, H., Su, L., Shi, C., Tang, X., Bednarz, B., and Xu, X. G., “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).

[22] Liu, T., Wolfe, N., Lin, H., Zieb, K., Ji, W., Caracappa, P., Carothers, C. D., and Xu, X. G., “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).

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

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

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

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

[27] Liu, T., Lin, H., Caracappa, P. F., and Xu, X. G., “Extension of a GPU/MIC based Monte Carlo Code, ARCHER, to internal radiation dose calculations,” *Health Physics, 109*(Supplement 1), p. S56, (2015).

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

[29] Liu, T., Su, L., Du, X., Lin, H., Zieb, K., Ji, W., Caracappa, P., and Xu, X. G., “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).

[30] Liu, T., Wolfe, N., Carothers, C. D., Ji, W., and Xu, X. G., “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).

[31] Liu, T., Wolfe, N., Carothers, C. D., Ji, W., and Xu, X. G., “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).

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

[33] Liu, T., Wolfe, N., Su, L., Carothers, C. D., Bednarz, B., and Xu, X. G., “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).

[34] Pi, Y., Feng, M., Huo, W., Zhang, L., Liu, T., Lin, H., Yang, L., Zheng, F., Tan, H., Pan, F., Chen, Z., and Xu, X. G., “Development of mesh-based age-dependent family phantoms,” presented at the 5th International Workshop on Computational Human Phantoms (CP2015), Seoul, Korea, (2015).

[35] Wolfe, N., Carothers, C. D., Liu, T., and Xu, X. G., “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).

[36] Du, X., Liu, T., Su, L., Caracappa, P. F., and Xu, X. G., “Extension of ARCHER Monte Carlo code to health physics dosimetry and shielding design: preliminary results,” *Health Physics, 107*(Supplement 1), p. S38, (2014).

[37] Du, X., Liu, T., Su, L., Ji, W., Caracappa, P. F., and Xu, X. G., “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).

[38] Huo, W., Liu, T., Su, L., Du, X., Chen, Z., and Xu, X. G., “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).

[39] Lin, H., Liu, T., Su, L., Du, X., Gao, Y., Caracappa, P. F., and Xu, X. G., “Formation of computational phantoms from CT numbers for use in the ARCHER Monte Carlo code,” *Health Physics, 107*(Supplement 1), p. S98, (2014).

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

[41] Liu, T., Du, X., Su, L., Gao, Y., Ji, W., Zhang, D., Shi, J. Q., Liu, B., Kalra, M. K., and Xu, X. G., “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).

[42] Liu, T., Du, X., Su, L., Ji, W., and Xu, X. G., “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).

[43] Liu, T., Su, L., Du, X., Caracappa, P. F., and Xu, X. G., “Comparison of accuracy and speed of ARCHER with MCNP for organ dose calculations from external photon beams under standard irradiation geometries,” *Health Physics, 107*(Supplement 1), p. S114, (2014).

[44] Liu, T., Su, L., Du, X., Lin, H., Zieb, K., Ji, W., Caracappa, P., and Xu, X. G., “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).

[45] Wolfe, N., Liu, T., Carothers, C., and Xu, X. G., “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. [download]

[46] Du, X., Liu, T., Ji, W., Xu, X. G., and Brown, F. B., “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.

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

[48] Liu, T., Du, X., Ji, W., Xu, X. G., and Brown, F. B., “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). [download]

[49] Liu, T., Du, X., and Xu, X. G., “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).

[50] Liu, T., Ji, W., and Xu, X. G., “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).

[51] Liu, T., Xu, X. G., and Carothers, C. D., “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).

[52] Riblett, M. J., Liu, T., Ji, W., and Xu, X. G., “Use of hardware accelerators for Monte Carlo-based neutron radiation transport: a preliminary study,” *Health Physics, 105*(Supplement 1), p. S99, (2013).

[53] Su, L., Du, X., Liu, T., and Xu, X. G., “A fast Monte Carlo electron transport code for dose calculations using the GPU accelerator,” *Health Physics, 105*(Supplement 1), p. S41, (2013).

[54] Su, L., Du, X., Liu, T., and Xu, X. G., “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).

[55] Su, L., Du, X., Liu, T., and Xu, X. G., “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).

[56] Xu, X. G., Liu, T., Su, L., Du, X., Riblett, M., Ji, W., and Brown, F. B., “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).

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

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

[59] Liu, T., Ding, A., Ji, W., Xu, X. G., Carothers, C. D., and Brown, F. B., “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).

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

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

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

[63] Su, L., Liu, T., Ding, A., and Xu, X. G., “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).

[64] Su, L., Liu, T., Ding, A., and Xu, X. G., “GPU/CUDA-based Monte Carlo methods for radiation protection dose calculations involving X-ray and proton sources,” *Health Physics, 103*(Supplement 1), p. S78, (2012).

[65] Ding, A., Liu, T., Liang, C., Ji, W., Shepard, M. S., Xu, X. G., and Brown, F. B., “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).

[66] Liu, T., Ding, A., Caracappa, P. F., and Xu, X. G., “Modeling of obese individuals using automatic deformation of mesh-based computational phantoms,” *Health Physics, 101*(Supplement 1), p. S34, (2011).

[67] Mille, M., Ding, A., Liu, T., Na, Y., Caracappa, P. F., and Xu, X. G., “The effect of patient obesity on PET/CT imaging dose using a phantom with a body mass index of 45,” *Health Physics, 101 *(Supplement 1), p. S31, (2011).

[68] Xu, X. G. and Liu, T., “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).

[69] Liu, T., Mille, M., Caracappa, P. F., Xu, X. G., Nour, S., and Inn, K., “A software solution to bioassay detector calibration using a library of virtual phantoms,” *Health Physics, 99*(Supplement 1), p. S78, (2010).