脑功能成象是研究脑科学和生命科学的重要工具,在对脑功能图象进行统计分析时,有必要对时间序列脑功能成象中的图象进行配准,研究采用修正的Gauss-Newton最优化方法,通过计算配准图象之间残差平方和的极值,实现了时间序列脑功能图象的高精度配准.

Brain functional imaging is a kind of important tools in study of brain and life science. It is necessary to register the time series images of brain functional imaging when doing statistical analysis for image data. In this paper, we adopt a modified Gauss-Newton optimization method to find out higher accurate registration of the time series brain functional images by calculating the minimum standard deviation between the registered images.