Hoh C K, Dahlbom M, Harris G, Choi Y, Hawkins R A, Phelps M E, Maddahi J
Department of Molecular and Medical Pharmacology, University of California, Los Angeles.
J Nucl Med. 1993 Nov;34(11):2009-18.
Two types of image similarity measures, the sum of absolute differences (SAD) and the stochastic sign change (SSC), were compared for three-dimensional registration of images from PET. To test the accuracy of both registration methods, 30 FDG brain studies, 40 13N-ammonia cardiac studies and 20 FDG liver tumor studies (where each image set contained 15 image planes, 128 x 128 pixels per plane) were made into worse case conditions by creating image sets of low counts and extreme defects. These images were then registered to the reference images that had been moved in three dimensions into a random set of known translations, rotations and normalization factors (x, y, z, theta, rho, sigma, nf). Neither method required any external fiduciary markers or operator interventions to register a set of images. The optimization of the image similarity (using the SAD or SSC) was performed with the simplex method and registration was completed within 10 min of computation time on a low-end workstation. Overall, the SAD method had an average inplane (x, y) registration error of 0.5 +/- 0.5 mm, a z-axis registration error of 1.1 +/- 1.1 mm, an inplane rotational error of 0.5 +/- 0.4 degrees, an out-of-plane rotational error of 1.1 +/- 1.2 degrees and a normalization factor error of 0.015 +/- 0.016. The SSC method had an average inplane (x, y) registration error of 0.6 +/- 0.5 mm, a z-axis registration error of 1.1 +/- 1.1 mm, an inplane rotational error of 0.7 +/- 0.5 degrees, an out-of-plane rotational error of 1.0 +/- 1.2 degrees and a normalization factor error of 0.014 +/- 0.014. This study demonstrates that either the SAD or SSC method for measuring image similarity, combined with the simplex method for function optimization, are accurate methods for registration of a wide variety of PET images including low count studies and those with marked interval changes in the pattern of count distribution.
为了对正电子发射断层扫描（PET）图像进行三维配准，比较了两种图像相似性度量方法，即绝对差之和（SAD）和随机符号变化（SSC）。为了测试两种配准方法的准确性，通过创建低计数和极端缺陷的图像集，将30例氟代脱氧葡萄糖（FDG）脑部研究、40例氮-13氨心脏研究和20例FDG肝脏肿瘤研究（其中每个图像集包含15个图像平面，每个平面128×128像素）设置为更差的情况。然后将这些图像与已在三维空间中移动到一组随机的已知平移、旋转和归一化因子（x、y、z、θ、ρ、σ、nf）的参考图像进行配准。两种方法都不需要任何外部基准标记或操作员干预来配准一组图像。使用单纯形法对图像相似性（使用SAD或SSC）进行优化，并在低端工作站上10分钟的计算时间内完成配准。总体而言，SAD方法的平均平面内（x、y）配准误差为0.5±0.5毫米，z轴配准误差为1.1±1.1毫米，平面内旋转误差为0.5±0.4度，平面外旋转误差为1.1±1.2度，归一化因子误差为0.015±0.016。SSC方法的平均平面内（x、y）配准误差为0.6±0.5毫米，z轴配准误差为1.1±1.1毫米，平面内旋转误差为0.7±0.5度，平面外旋转误差为1.0±1.2度，归一化因子误差为0.014±0.014。这项研究表明，用于测量图像相似性的SAD或SSC方法，与用于函数优化的单纯形法相结合，是对包括低计数研究和计数分布模式有明显间隔变化的研究在内的各种PET图像进行配准的准确方法。
