Dan Nguyen, Ph.D., is a scientist with expertise in radiation therapy treatment planning, deep learning, and optimization techniques and algorithms. He completed his Ph.D. in Biomedical Physics in 2017 at the University of California Los Angeles (UCLA), where he worked extensively on 4π Radiotherapy, Fluence Map Optimization, and Direct Aperture Optimization techniques under the guidance and mentorship of Dr. Ke Sheng.
Dr. Nguyen was recruited to the Division of Medical Physics and Engineering, Department of Radiation Oncology at UT Southwestern in 2017 as a faculty member. He was a founding member of the multiple-investigator lab called the Medical Artificial Intelligence and Automation (MAIA) Laboratory, which was focused to innovate, develop, and apply artificial intelligence technologies to empower clinicians—especially those with less experience or limited resources—for improved patient care. He works very closely with Dr. Steve Jiang in researching and applying deep learning technologies to various facets of radiotherapy, including treatment planning, medical imaging, and outcome prediction.
- University of Texas-Austin (2012), Physics
- Graduate School
- Uni of California (UCLA) (2015), Biomedical Physics
- Graduate School
- Uni of California (UCLA) (2017), Biomedical Physics
- Artificial Intelligence
- Deep Learning
- Optimization Techniques and Algorithms
- Radiation Therapy
- Incorporating human and learned domain knowledge into training deep neural networks: A differentiable dose-volume histogram and adversarial inspired framework for generating Pareto optimal dose distributions in radiation therapy.
- Nguyen D, McBeth R, Sadeghnejad Barkousaraie A, Bohara G, Shen C, Jia X, Jiang S, Med Phys 2019 Dec
- A Fast Deep Learning Approach for Beam Orientation Optimization for Prostate Cancer Treated with Intensity Modulated Radiation Therapy.
- Sadeghnejad Barkousaraie A, Ogunmolu O, Jiang S, Nguyen D, Med Phys 2019 Dec
- Three-Dimensional Dose Prediction for Lung IMRT Patients with Deep Neural Networks: Robust Learning from Heterogeneous Beam Configurations.
- Barragán-Montero AM, Nguyen D, Lu W, Lin M, Norouzi-Kandalan R, Geets X, Sterpin E, Jiang S, Med Phys 2019 May
- Three-dimensional radiotherapy dose prediction on head and neck cancer patients with a hierarchically densely connected U-net deep learning architecture.
- Nguyen D, Jia X, Sher D, Lin MH, Iqbal Z, Liu H, Jiang SB Phys Med Biol 2019 Jan
- A feasibility study for predicting optimal radiation therapy dose distributions of prostate cancer patients from patient anatomy using deep learning.
- Nguyen D, Long T, Jia X, Lu W, Gu X, Iqbal Z, Jiang S Sci Rep 2019 Jan 9 1 1076
- Technical Note: A feasibility study on deep learning-based radiotherapy dose calculation.
- Xing Y, Nguyen D, Lu W, Yang M, Jiang S, Med Phys 2019 Dec
- Generating synthesized computed tomography (CT) from cone-beam computed tomography (CBCT) using CycleGAN for adaptive radiation therapy.
- Liang X, Chen L, Nguyen D, Zhou Z, Gu X, Yang M, Wang J, Jiang SB, Phys Med Biol 2019 May
- Intelligent inverse treatment planning via deep reinforcement learning, a proof-of-principle study in high dose-rate brachytherapy for cervical cancer.
- Shen C, Gonzalez Y, Klages P, Qin N, Jung H, Chen L, Nguyen D, Jiang SB, Jia X, Phys Med Biol 2019 Apr
- Fully automated organ segmentation in male pelvic CT images.
- Balagopal A, Kazemifar S, Nguyen D, Lin MH, Hannan R, Owrangi A, Jiang S Phys Med Biol 2018 Dec 63 24 245015
- VMAT optimization with dynamic collimator rotation.
- Lyu Q, O'Connor D, Ruan D, Yu V, Nguyen D, Sheng K Med Phys 2018 Apr
- American Association of Physicists in Medicine (2013)