Zhuoran Jiang, PhD
Biography
Zhuoran Jiang is from Harbin, the ‘ice city’, in China. She received her B.S. and M.S. in Electronic Science and Engineering from Nanjing University, China. She obtained her Ph.D. in Medical Physics from Duke University, USA, in 2024. Zhuoran’s research focuses on artificial intelligence for radiation therapy, including image guidance and in-vivo dose verification. In her free time, she enjoys baking, hiking, and playing video games.
Zhuoran joined the Stanford University Medical Physics Residency in 2024.
Publications
Zhang, Y., Jiang, Z., Zhang, Y., & Ren, L. (2024). A review on 4D cone‐beam CT (4D‐CBCT) in radiation therapy: Technical advances and clinical applications. Medical Physics, accepted.
Jiang, Z., Wang, S., Xu, Y., Sun, L., Gonzalez, G., Chen, Y., Wu, Q. J., Xiang L., & Ren, L. (2023). Radiation-induced Acoustic Signal Denoising using a Supervised Deep Learning Framework for Imaging and Therapy Monitoring. Physics in Medicine & Biology, 68(23). DOI: 10.1088/1361-6560/ad0283.
Lang, Y., Jiang, Z., Sun, L., Xiang, L., & Ren, L. (2023). Hybrid-Supervised Deep Learning for Domain Transfer 3D Protoacoustic Image Reconstruction. arXiv preprint arXiv:2308.06194.
Jiang, Z., Polf, J. C., Barajas, C. A., Gobbert, M. K., & Ren, L. (2023). A feasibility study of enhanced prompt gamma imaging for range verification in proton therapy using deep learning. Physics in Medicine & Biology, 68(7), 075001.
Jiang, Z., Sun, L., Yao, W., Wu, Q. J., Xiang, L., & Ren, L. (2022). 3D in vivo dose verification in prostate proton therapy with deep learning-based proton-acoustic imaging. Physics in Medicine & Biology, 67(21), 215012.
Jiang, Z., Chang, Y., Zhang, Z., Yin, F. F., & Ren, L. (2022). Fast four‐dimensional cone‐beam computed tomography reconstruction using deformable convolutional networks. Medical Physics, 49(10), 6461-6476.
Zhang, Z., Jiang, Z., Zhong, H., Lu, K., Yin, F. F., & Ren, L. (2022). Patient‐specific synthetic magnetic resonance imaging generation from cone beam computed tomography for image guidance in liver stereotactic body radiation therapy. Precision Radiation Oncology, 6(2), 110-118.
Zhang, Z., Huang, M., Jiang, Z., Chang, Y., Lu, K., Yin, F. F., ... & Ren, L. (2022). Patient-specific deep learning model to enhance 4D-CBCT image for radiomics analysis. Physics in Medicine & Biology, 67(8), 085003.
Jiang, Z., Zhang, Z., Chang, Y., Ge, Y., Yin, F. F., & Ren, L. (2021). Enhancement of 4-D Cone-Beam Computed Tomography (4D-CBCT) Using a Dual-Encoder Convolutional Neural Network (DeCNN). IEEE Transactions on Radiation and Plasma Medical Sciences, 6(2), 222-230.
Jiang, Z., Zhang, Z., Chang, Y., Ge, Y., Yin, F. F., & Ren, L. (2021). Prior image-guided cone-beam computed tomography augmentation from under-sampled projections using a convolutional neural network. Quantitative imaging in medicine and surgery, 11(12), 4767.
Peng, T., Jiang, Z., Chang, Y., & Ren, L. (2021). Real-Time Markerless Tracking of Lung Tumors Based on 2-D Fluoroscopy Imaging Using Convolutional LSTM. IEEE Transactions on Radiation and Plasma Medical Sciences, 6(2), 189-199.
Chang, Y., Jiang, Z., Segars, W. P., Zhang, Z., Lafata, K., Cai, J., ... & Ren, L. (2021). A generative adversarial network (GAN)-based technique for synthesizing realistic respiratory motion in the extended cardiac-torso (XCAT) phantoms. Physics in Medicine & Biology, 66(11), 115018.
Zhang, Z., Huang, M., Jiang, Z., Chang, Y., Torok, J., Yin, F. F., & Ren, L. (2021). 4D radiomics: impact of 4D-CBCT image quality on radiomic analysis. Physics in Medicine & Biology, 66(4), 045023.
Sun, L., Jiang, Z., Chang, Y., & Ren, L. (2021). Building a patient-specific model using transfer learning for four-dimensional cone beam computed tomography augmentation. Quantitative Imaging in Medicine and Surgery, 11(2), 540.
Jiang, Z., Yin, F. F., Ge, Y., & Ren, L. (2021). Enhancing digital tomosynthesis (DTS) for lung radiotherapy guidance using patient-specific deep learning model. Physics in Medicine & Biology, 66(3), 035009.
Jiang, Z., Yin, F. F., Ge, Y., & Ren, L. (2020). A multi-scale framework with unsupervised joint training of convolutional neural networks for pulmonary deformable image registration. Physics in Medicine & Biology, 65(1), 015011.
Chen, Y., Yin, F. F., Jiang, Z., & Ren, L. (2019). Daily edge deformation prediction using an unsupervised convolutional neural network model for low dose prior contour based total variation CBCT reconstruction (PCTV-CNN). Biomedical physics & engineering express, 5(6), 065013.
Shieh, C. C., Gonzalez, Y., Li, B., Jia, X., Rit, S., Mory, C., ... & Keall, P. (2019). SPARE: Sparse‐view reconstruction challenge for 4D cone‐beam CT from a 1‐min scan. Medical physics, 46(9), 3799-3811.
Jiang, Z., Chen, Y., Zhang, Y., Ge, Y., Yin, F. F., & Ren, L. (2019). Augmentation of CBCT reconstructed from under-sampled projections using deep learning. IEEE transactions on medical imaging, 38(11), 2705-2715.
Awards and Honors
- AAPM Research Seed Funding Grant, The American Association of Physicists in Medicine (AAPM), 2024
- AAPM/RSNA Doctoral Graduate Fellowships, The American Association of Physicists in Medicine (AAPM), 2023
- John R. Cameron Young Investigator Symposium Finalist, AAPM 63rd Annual Meeting, Virtual, 2021 (First and presenting author)