On July 21, the final round of the Zhejiang International College Students’ Innovation Competition 2024 was held at Hangzhou Normal University, with participation from 113 universities, 51,900 projects, and 390,000 participants. Three projects, instructed by our faculty and involving students from the School of Mathematical Sciences and other colleges, advanced to the finals and secured two gold and one silver medals, marking the best performance in the College’s history at this event.
【Industry Track – Industry-Education Collaborative Innovation Group】
Project: Algorithm and Device for Accurate Quantitative Analysis of Human Scarred Blood Vessels
Award: Gold Medal in Industry Track - Industry-Education Collaboration and Innovation Group
Instructors: Zhang Jianfeng, Liu Jingdi
Participants: Shao Yuan, Liu Heyao, Shi Kaibing, Huang Qianyao, Hu Nannan, Jiang Yinuo, Cheng Ran, Yang Lei, Wan Zixin, Zheng Yangzong, Shi Liting, Weng Yidong
Project Description: Addressing current challenges in imaging scarred blood vessels, including inaccurate imaging, limited detection depth, and imaging latency, the team conducted research in medical artificial intelligence and developed an algorithm and device for accurate quantitative analysis of scarred blood vessels. Leveraging three core technologies, including an optimization algorithm for vascular system imaging based on biological mechanisms, the team successfully developed an engineering prototype that provides more accurate, deeper, and faster imaging. The results have been well-received by enterprises and society.
【Undergraduate Innovation Group】
Intelligent Imaging Technology—Nationwide Premier Supplier of Biomechanical Vascular Imaging Devices
Award: Gold Medal in Undergraduate Innovation Group
Instructors: Zhang Jianfeng, Liu Jingdi
Participants: Huang Qianyao, Shi Kaibing, Lin Xiaohan, Xiong Sichen, Cai Yeyun, Zhao Ruoxi, Li Qinxin, Xu Xinya, Wang Xinyun, Wang Yueyang, Lin Yirong, Shen Qiyue, Luo Haojun, Chen Ling'er, Su Yankai
Project Description: The Intelligent Imaging Team aims to address medical scenarios requiring vascular identification, such as intravenous therapy, puncture, and surgical identification. To tackle the challenges in the current vascular imaging device industry, the team innovatively integrates biological mechanisms with new data-driven models. By applying their self-developed algorithms, they have successfully developed a vascular imaging device with high accuracy, deep probing capabilities, and low latency.
Smart Monitoring of Heart Health—AI-Driven Non-Invasive Coronary Heart Disease; Full-Cycle Precision Monitoring Pioneer
Award: Silver Medal in Undergraduate Innovation Group
Instructors: Ge Xinyang, Liu Jingdi, Xu Hao, Chen Xiaorong
Participants: Zhang Li, Zhang Qixin, Wang Xuyan, Feng Jinyi, Luo Yiming, Wu Qinyi, Pei Yuhang, Du Ketao, Ye Xingpeng, Liu Fei, Wang Xian, Yang Na, Zhang Jiajun, Zhao Xinyi, Zhu Mengyuan
Project Introduction: The “Smart Monitoring of Heart Health” project focuses on the prevention and treatment of cardiovascular diseases. Addressing the low screening rate of coronary heart disease in local communities and insufficient patient follow-up, the project aims to establish an AI-driven, non-invasive coronary heart disease full-cycle monitoring system. By leveraging interdisciplinary strengths, it promotes early diagnosis and treatment of coronary heart disease in local communities.
