Multimodal Image Registration Using Mean and Variance of Joint Intensity Distribution

摘要：

Mean and variance are used as two of several import descriptors of distribution in probability theory and statistics. In this paper, we present several new intensity-based multimodal image registration methods using mean and variance of data. Partition intensity uniformity (PIU) is the first successful medical multimodal image registration algorithm. PIU method will be illconditioned when the mean of intensity of voxels, which positions in one image are correspond to given intensity value in another image, is very small. A new adjustable parameter alpha is introduced into PIU. What is more, mean parameter that refers to as expectation is removed off from PIU function, then two new different PIU measures are proposed. These new similarity measures are preliminarily validated by multi-modal medical image data registering experiments from calculating time, robustness to noise and influence of image window overlapping region. The results of tests show the new modified PIU metric may have better performance.

关键词： image registration multimodal image registration measure intensity cluster

作者: Yonggang Shi

作者单位: School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China

会议类型: 国际会议

会议名称: 2010 IEEE 10th International Conference on Signal Processing(第十届信号处理国际会议 ICSP 2010)

会议地点: 北京

会议语种:英文

页码: 940-943

在线出版日期: 2010-08-24（万方平台首次上网日期，不代表论文的发表时间）