勷勤数学•杰出学者报告

题      目：Knowledge-Guided Deep Learning for Enhanced Medical Image Segmentation

报  告  人：陈延伟 教授  (邀请人：叶颀)

                                    日本立命馆大学        

时      间：3月10日  10：00-11：00

地     点：数科院西楼111报告厅

报告人简介:

        陈延伟教授，1985 年日本神户大学毕业，1990 年日本大阪大学博士毕业，工学博士。曾任日本激光給合技衍研究所研究员、日本琉球大学讲师、副教授，教授。日本立命馆大学信息理工学院终身教授，立命館大学尖端医学健康信息研究中心创始人和第一任中心主任。2024 年 4 月当选日本工程院外籍院士。研究领域为计算机视觉，计算解剖学，人工智能。在 IEEE Transactions on Image Processing, IEEE Transactions on Medical Imaging, CVPR, ICCV，IJCAI，AAAI 等顶级期刊和国际会议发表论文 200 多篇。获得 ICPR2013 最佳科学论文奖、JAMIT 最优论文奖、中科院杰出海外华人科学家基金。根据斯坦福大学/爱思唯尔的排名，在单个最近一年和整个职业生涯的科学家中均排名世界前 2%。作为 PI 主持近 20 项日本政府基金项目和国际合作项目。

摘      要：

       Recently, Deep Learning (DL) has played an important role in various academic and industrial domains, especially in computer vision and image recognition. Although deep learning (DL) has been successfully applied to medical image analysis, achieving state-of-the-art performance, few DL applications have been successfully implemented in real clinical settings. The primary reason for this is that the specific knowledge and prior information of human anatomy possessed by doctors is not utilized or incorporated into DL applications. In this keynote address, I will present our recent advancements in knowledge-guided deep learning for enhanced medical image analysis. This will include two research topics: (1) our proposed deep atlas prior, which incorporates medical knowledge into DL models; (2) language-guided medical image segmentation, which incorporates the specific knowledge of doctors as an additional language modality into DL models.

          欢迎老师、同学们参加、交流！