Fang-Fang Yin, PhD

Gustavo S. Montana Distinguished Professor of Radiation Oncology
Professor in Radiation Oncology
Director of the Medical Physics Graduate Program at Duke Kunshan University
Professor of Medical Physics at Duke Kunshan University
Member of the Duke Cancer Institute
Address: Box 3295 DUMC
Durham, NC 27710
Phone: (919) 660-2185
Email: fangfang.yin@duke.edu

Research Interests

Stereotactic radiosurgery, Stereotactic body radiation therapy, treatment planning optimization, knowledge guided radiation therapy, intensity-modulated radiation therapy, image-guided radiation therapy, oncological imaging and informatics

Publications

Jiang, Z., et al. “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, vol. 6, no. 2, Feb. 2022, pp. 222–30. Scopus, doi:10.1109/TRPMS.2021.3133510.

Wang, Wentao, et al. “Transfer learning for fluence map prediction in adrenal stereotactic body radiation therapy.” Phys Med Biol, vol. 66, no. 24, 2021. Pubmed, doi:10.1088/1361-6560/ac3c14.

Jiang, Zhuoran, et al. “Prior image-guided cone-beam computed tomography augmentation from under-sampled projections using a convolutional neural network.” Quant Imaging Med Surg, vol. 11, no. 12, Dec. 2021, pp. 4767–80. Pubmed, doi:10.21037/qims-21-114.

Sheng, Yang, et al. “Artificial intelligence applications in intensity modulated radiation treatment planning: an overview.” Quant Imaging Med Surg, vol. 11, no. 12, Dec. 2021, pp. 4859–80. Pubmed, doi:10.21037/qims-21-208.

Zhang, Lei, et al. “Multi-contrast four-dimensional magnetic resonance imaging (MC-4D-MRI): Development and initial evaluation in liver tumor patients.” Medical Physics, vol. 48, no. 12, Dec. 2021, pp. 7984–97. Epmc, doi:10.1002/mp.15314.

Hito, Martin, et al. “Assessing the robustness of artificial intelligence powered planning tools in radiotherapy clinical settings-a phantom simulation approach.” Quant Imaging Med Surg, vol. 11, no. 12, Dec. 2021, pp. 4835–46. Pubmed, doi:10.21037/qims-21-51.

Li, Xinyi, et al. “Insights of an AI agent via analysis of prediction errors: a case study of fluence map prediction for radiation therapy planning.” Phys Med Biol, vol. 66, no. 23, Nov. 2021. Pubmed, doi:10.1088/1361-6560/ac3841.

Wang, C., et al. “A Dosimetric Study Comparing Two Beam Arrangement Strategies in Fractionated Thoracic Spine Stereotactic Body Radiotherapy (SBRT) Planning.” International Journal of Radiation Oncology, Biology, Physics, vol. 111, no. 3S, 2021, p. e557. Epmc, doi:10.1016/j.ijrobp.2021.07.1510.