Chenchu Xu
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Chenchu Xu [Google Scholar] [Anhui University]
Associate Professor |
I am an associate professor at School of Computer Science and Technology, Anhui University (AHU). Before joining AHU, I was a postdoc at Schulich School of Medicine & Dentistry, Western University (UWO), Canada, working with Prof. Shuo Li. I obtained the Ph.D in computer Science from Anhui University and the M.Sc. degree in computer science from the Hefei University of Technology and the B.Sc. degree in network engineering from the University of Electronic Engineering
I am always looking for highly-motivated students with strong mathematical background or excellent coding skills. If you are interested in working with me, please send me an email about your interests and background (attaching your CV, transcripts, and any previous research papers).
Research Interests
Lie in the areas of Computer Vision, Machine Learning, and Medical Image Analysis. To enable artificial intelligence to change the practice of medicine; Seek to enable artificial intelligence to move out of the lab and into real clinic settings.
News
04/2024, Our latest research, 'Deep Generative Adversarial Reinforcement Learning for Semi-Supervised Segmentation of Low-Contrast and Small Objects in Medical Images,' has been published in IEEE Transactions on Medical Imaging!
10/2023, Our research was distinguished with notable recognition, being featured as the Runner-Up for the Best Paper Award in the Elsevier-MedIA MICCAI 2022 Special Issue. [Click for details]
10/2023, Our master's students, Jinhao Liu and Xinglai Zhu, as first and second authors, have published their innovative research, 'Accurate 3D contrast-free myocardial infarction delineation using a 4D dual-stream spatiotemporal feature learning framework,' in Applied Soft Computing！
09/2023, We're delighted to announce our paper, 'Spatiotemporal Knowledge Teacher-Student Reinforcement Learning to Detect Liver Tumors Without Contrast Agents,' has been accepted by Medical Image Analysis, heralding a pivotal advance in non-invasive liver tumor detection methods!
07/2023, Thrilled to share that as the corresponding author, our latest work 'Heuristic multi-modal integration framework for liver tumor detection from multi-modal non-enhanced MRIs' has been published in Expert Systems with Applications!
05/2023, Thrilled to announce that Ph.D. student Yuhui Song’s paper, 'Multi-shot Prototype Contrastive Learning and Semantic Reasoning for Medical Image Segmentation,' has secured an early acceptance by MICCAI 2023!
03/2023, Our master's student, Yuan Yang, has published innovative research, 'Dual uncertainty-guided mixing consistency for semi-supervised 3d medical image segmentation,' in IEEE Transactions on Big Data!