矢/冠状图像重建的随机迭代函数系统算法  

Reconstruction of sagittal and coronal images based on the iterated fuction system with probability

作　　者：曲桂红[1] 张大力[1] 阎平凡[1] 

机构地区：[1]清华大学自动化系,北京100084

出　　处：《清华大学学报（自然科学版）》2001年第3期97-100,共4页Journal of Tsinghua University(Science and Technology)

基　　金：北京市科技新星计划基金项目! (95 18710 0 )

摘　　要：为重建高质量的矢 /冠状图像 ,以满足医生在临床诊断与治疗时更加准确地掌握患者组织器官及病灶形态的分布情况 ,采用随机迭代函数系统 (IFS)算法对序列 CT/MRI断层图像进行分形插值计算 ,提出了基于插值曲线型值采样点序列波形局部网格分形维 ,实现对仿射中的垂直尺度因子的估计方法。实验结果表明 ,采用该算法进行插值计算 ,可较好地保留图像的纹理特征 ,获得高分辨率图像。算法占用内存少、计算速度快、精度高 ,可推广应用于一般的灰度图像插值计算。High quality coronal and sagittal images are needed to help doctors accarately locate the structures and locations around organs and focal lesions in patients for clinic diagnosis and treatment. A set of CT/MRI images were interpolated using the fractal geometry interpolation algorithm based on the iterated function system (IFS). The vertical scaling factors of the IFS were estimated according to the local box dimension of the sample data set. The experiments showed that the texture of the interpolated images can be retained with high resolution. There are many advantages of the algorithm, i.e. reducing memory and time; getting precise images. The algorithm can also be applied for interpolating general grey level images .

关 键 词：图像重建 迭代函数系统 矢/冠状图像 网格分维计算 垂直尺度因子 分形插值 插值函数 断层图像 

分 类 号：R814.42[医药卫生—影像医学与核医学] TP391.41[医药卫生—放射医学]