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Yufeng Cao, PhD

Academic Title:

Post Doc Fellow

Primary Appointment:

Radiation Oncology


685 W Baltimore St

Phone (Primary):




Education and Training

2011-2013       M.S., Applied Mathematics, University of Texas-Pan American

2014-2019       Ph.D., Applied Mathematics, Washington State University

2019-2021       Post-Doctoral Fellowship, Radiation Oncology, Keck School of Medicine,                                            University of Southern California


Dr. Cao is a post-doctoral fellow in Dr. Lei Ren's lab. He received his Ph.D. in 2019 at Washington State University, with a major in mathematics and computer science. His interest is in medical imaging segmentation, clinical decision-making, and outcomes predictions by using deep learning and machine learning. He currently works on radiomic imaging biomarkers derived from PSMA-PET acquired pre- and post-MDT for metastasis-free survival (MFS) prediction, which may provide better features to discriminate response in the future to improve the outcome of these patients.  

Research/Clinical Keywords

Clinical decision-making, outcomes prediction, medical imaging segmentation.

Highlighted Publications

  • Y Cao, D Kunaprayoon, and L Ren. Interpretable AI-assisted Clinical Decision Making (CDM) for dose prescription in radiosurgery of brain metastases. Radiotherapy and Oncology 2023: 109842.
  • Y Cao, D Kunaprayoon, J Xu, and L Ren. AI-assisted Clinical Decision Making (CDM) for dose prescription in radiosurgery of brain metastases using three-path three-dimensional CNN. Clinical and Translational Radiation Oncology 2023: 100565.
  • A Vassantachart, Y Cao, Z Shen, K Cheng, M Gribble, J Ye, G Zada, K Hurth, A Mathew, S Guzman, & W Yang. Segmentation and Classification of Grade I and II Meningiomas from Magnetic Resonance Imaging: An Open Annotated Dataset (Meningioma-SEG-CLASS). Cancer Imaging Arch. Published online 2023. doi:10.7937/0TKV-1A36
  • Y Cao, A Vassantachart, M Gribble, S Guzman, K Hurth, J Ye, G Zada, E L Chang, W Yang. Automatic differentiate the meningiomas grade on magnetic resonance image using asymmetric convolutional neural network. Scientific Reports. 2022 9; 12(1): 1-9. (Co-first authors)
  • Y Cao, A Vassantachart, O Ragab, S Bian, P Mitra, Z Xu, J Cui, A Z Gallogly, Z L Shen, S Balik, M Gribble, E L Chang, W Yang. Automatic segmentation of high-risk clinical target volume for tandem-and- voids brachytherapy patients using a novel dual-path convolutional neural network. Medical Physics. 2022; 49(3): 1712-1722.
  • Y Cao, A Vassantachart, J Ye, Y Cheng, D Ruan, K Sheng, Y Lao, Z Shen, S Balik, S Bian, G Zada, A Shiu, E L Chang, W Yang. Automatics detection and segmentation of multiple brain metastases on MR images using asymmetric U-Net architecture. Phy. Med. Biol. 2021; 66:015003.

Awards and Affiliations

2021          First place of 2021 AAPM-SCC Norm Baily Award                            AAPM

2021          Featured article focusing on Medical Physics (PMID 33186927)         IOP Publishing