报告问题 (Title)：Medical Image Quality Enhancement and Segmentation with Deep Learning（基于深度学习的医学图像质量增强和支解）

报告人 (Speaker)：李智 特聘研究员（华东师范大学）

报告时间 (Time)：2023年11月2日(周四) 13:30

报告所在 (Place)：校本部 F420

约请人(Inviter)：温智婕

主理部分：理学院数学系

报告摘要：In this talk, we explore the domain of medical image analysis, where the influential impact of deep learning architectures comes to the forefront in addressing the intricate challenges posed by medical imaging. This methodology places significant emphasis on the vital necessity of capturing information at various scales to yield superior outcomes. Whether it's through the utilization of a recurrent gate module and a multi-scale module for polyp segmentation, the incorporation of an adaptive selection aggregation module to enhance feature fusion, or the integration of a dual-channel neural network that underscores the interactions between denoising and super-resolution tasks, which collectively underscore the transformative potential of deep learning.