报告题目：Enabling Graph Techniques for Medical Image Segmentation
报 告 人：巫晓东教授
时间：2016年5月12日上午9：30
地点：安徽大学磬苑校区理工D楼318室
主办单位：计算机科学与技术学院
欢迎各位老师、同学届时前往！
科学技术处
2016年5月10日
报告内容简介：
To usher in a new era of Precision Medicine, imaging is playing an increasingly significant role, with its superior capability of phenotyping the physical manifestations of disease to establish cohorts and prognosticate responses to treatments and therapies. Meanwhile, this opportunity poses the great challenge of enhancing image processing technology to meet the new demands. Image segmentation is a fundamental problem in biomedical image processing and computer-aided diagnosis.Robust, efficient, and accurate automated segmentation methods are highly desirable for numerous biomedical studies and applications. In this talk, we present effective image segmentation techniques based on enabling graph algorithms for detecting biomedical objects in 3-D and higher dimensional images.The most recent advances are also discussed. In comparison with most known segmentation methods that suffer from their inability to attain globally optimal segmentation or lengthy computation time, our techniques produce, in an efficient manner, segmentation of optimal quality with respect to general cost functions on a wide range of biomedical objects with complex topological structures.Examples and segmentation results on various medical image datasets are shown.
报告人简介：
Xiaodong Wu received the BS and MS degrees both in Computer Science from Peking University,