Wenyu Xing-智慧医疗超声实验室

Wenyu Xing

Department: Institute of Biomedical Engineering and Technology
Office: Room 1301, Building D2, Bay Valley Science and Technology Park
Title: Postdoc
Email: wyxing@fudan.edu.cn

Education and Work Background

● 2023/06 - Now Fudan University, Academy for Engineering and Technology, Postdoctor (Supervisor: Professor Dean Ta)

● 2020/09 - 2023/06 Fudan University, Biomedical Engineering, Doctor of Engineering (Supervisor: Professor Dean Ta)

● 2017/09 - 2020/06 Shanghai University of Engineering Science, Intelligent Perception and Control, Master of Engineering

● 2013/09 - 2017/06 Shanghai Polytechnic University, Automation, Bachelor of Engineering

Research Direction

● Ultrasound imaging and medical image processing

● Multimodal and multi-omics intelligent diagnosis

Honors and Awards

● 2023 Shanghai "Super Postdoctoral" Incentive Plan

● 2023 Fudan University's "Super Postdoctoral" Incentive Plan

● Outstanding graduates from Fudan University in 2023

● 2020 Shanghai Outstanding Graduates

● 2019 Baowu Steel Education Fund Outstanding Student Award

● 2019 National Scholarship for Graduate Students

● 2017 Shanghai Outstanding Graduates

Scientific Research Project

● 74th batch of general funding project from China Postdoctoral Science Foundation, Research on the Theory and Method of Intelligent Diagnosis of ARDS Risk Classification using Pulmonary Ultrasound Imaging

● Key project of the National Natural Science Foundation of China, Research on New Mechanisms and Deep Information Mining Methods of Ultrasound Propagation and Regulation in Multi-layer Complex Biological Tissues

● Shanghai Science and Technology Major Project, Establishment of Critical Care Early Warning and Prediction System and Real World Research

● Fudan University Medical Engineering Integration Project, Research on Weak Supervised Segmentation and Characterization of Pneumonia CT Imaging Lesions Based on Transformer

Representative Papers

● WY Xing, ZB Zhu, DN Hou, et al., CM-SegNet: A deep learning-based automatic segmentation approach for medical images by combining convolution and multilayer perceptron. Computers in Biology and Medicine, 2022, 147: 105797.

● WY Xing, W He, XL Li, et al., Early severity prediction of BPD for premature infants from chest X-ray images using deep learning: A study at the 28th day of oxygen inhalation. Computer Methods and Programs in Biomedicine, 2022, 221: 106869.

● WY Xing, C He, JW Li, et al., Automated lung ultrasound scoring for evaluation of coronavirus disease 2019 pneumonia using two-stage cascaded deep learning model. Biomedical signal processing and control, 2022, 75: 103561.

● WY Xing, GN Li, C He, et al., Automatic detection of A‐line in lung ultrasound images using deep learning and image processing. Medical Physics, 2023, 50(1), 330-343.

● WY Xing, YW Liu, C He, et al., Frame-to-video-based Semi-supervised Lung Ultrasound Scoring Model. 2023 IEEE International Ultrasonics Symposium (IUS), 1-4.

● WY Xing, M Yu, Xin Liu, et al., A Mumford-Shah Model-based Method for Inpainting Markers in Ultrasound Images. 2023 International Congress on Ultrasonics (ICU), 1-6.

● T Jiang, WY Xing, M Yu, et al., A hybrid enhanced attention transformer network for medical ultrasound image segmentation. Biomedical Signal Processing and Control, 2023, 86: 105329.

● YW Liu, WY Xing, MB Zhao, et al., A new classification method for diagnosing COVID-19 pneumonia based on joint CNN features of chest X-ray images and parallel pyramid MLP-mixer module. Neural Computing and Applications, 2023, 35(23): 17187-17199.

● YW Liu, WY Xing, MB Zhao, et al., An end-to-end framework for diagnosing COVID-19 pneumonia via Parallel Recursive MLP module and Bi-LTSM correlation. 2023 Medical Imaging with Deep Learning, 198: 1-10.

● QH Huang, Y Lei, WY Xing, et al., Evaluation of pulmonary edema using ultrasound imaging in patients with COVID-19 pneumonia based on a non-local Channel attention ResNet. Ultrasound in medicine & biology, 2022, 48 (5), 945-953.

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