Sorting 4DCT Images Based on Manifold Learning

摘要：

Respiratory motion degrades anatomic position reproducibility, and result in significant errors in radiotherapy. 4D computed Tomography (4DCT) can characterize anatomy motion during breathing. Usually, the acquired 4DCT images sequences is out of order. How to rearrange the sequence, i.e. sort 4DCT images has been the focus of 4DCT. In this paper we propose a method based on manifold learning, lsomap technique to reconstruct time-resolved CT volumes. By mapping high dimensional image data with lsomap into low dimensional space, each image is assigned a value, then 4DCT images is sorted according to the value to reconstruct a respiratory cycle. Experiments result shows that the method is feasible to sort 4 DCT images without using any external motion monitoring systems.

作者: Zhaohui Luo Zaifang Xi Junnian Wang Dongfeng Tang

作者单位: College of Information and Electric Engineering Hunan University of Science and Technology Xiangtan, P. R. China

会议类型: 国际会议

会议名称: International Conference on Intelligent Computation Technology and Automation(2008 智能计算技术与自动化国际会议 ICICTA 2008)

会议地点: 长沙

会议语种:英文

页码: 1472-1476

在线出版日期: 2008-10-20（万方平台首次上网日期，不代表论文的发表时间）