于妍妍，博士，2018年获得香港城市大学电子工程系博士学位，获评深圳市海外高层次人才（C类），2020年加入深圳大学医学部生物医学工程学院。研究方向为高分辨超声成像、超声人工智能影像算法及设备研究。

 主持项目：

[1]. 国家自然科学基金青年科学基金，11804357，超分辨超声成像的微泡声学特性与识别方法研究，2019/01-2021/12，29万元，(在研)。
[2]. 中国博士后科学基金，2018M643259，基于超分辨超声的小动物脑血流成像方法研究，2019/01-2020/12，5万元， （结题）。

 代表成果：

[1] [Zheng, X., Yao, Z. , Huang, Y. Yu], Y. , Wang, Y., Liu, Y., Mao, R., Li, F., Xiao, Y., Wang, Y. and Hu, Y., Deep learning radiomics can predict axillary lymph node status in early-stage breast cancer. Nature Communications, 11(1), pp.1-9, 2020.

[2] Yu Y, Zhang Z, Cai F, Su M, Jiang Q, Zhou Q, Humayun MS, Qiu W, Zheng H. A Novel Racing Array Transducer for Noninvasive Ultrasonic Retinal Stimulation: A Simulation Study. Sensors. 2019 Jan;19(8):1825.

[3] [Hong J, Su M, Yu Y], Zhang Z, Liu R, Huang Y, Mu P, Zheng H, Qiu W. A dual-mode imaging catheter for intravascular ultrasound application. IEEE transactions on medical imaging. 2018 Sep 12;38(3):657-63.

[4] Y. Yu, Y. Xiao, and B. Chiu, "Breast lesion classification based on supersonic shear-wave elastography and automated lesion segmentation from B-mode ultrasound images," Computers in Biology and Medicine, vol. 93, pp.31-46, 2018. .

[5] Y. Yu, Y. Chen, and B. Chiu, "Fully automatic prostate segmentation from transrectal ultrasound images based on radial bas-relief initialization and slice-based propagation," Computers in Biology and Medicine, vol. 74, pp.74-90, 2016.