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REGULARIZED SURFACE AND POINT LANDMARKS BASED EFFICIENT NON-RIGID MEDICAL IMAGE REGISTRATION

机译:基于有效的非刚性医学图像注册的常规表面和点地标

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摘要

Medical image registration is one of the fundamental tasks in medical image processing. It has various applications in field of image guided surgery (IGS) and computer assisted diagnosis (CAD). A set of non-linear methods have been already developed for inter-subject and intra-subject 3D medical image registration. However, efficient registration in terms of accuracy and speed is one of the most demanded of today surgical navigation (SN) systems. This paper is a result of a series of experiments which utilizes Fast Radial Basis Function (RBF) technique to register one or more medical images non-rigidly. Initially, a set of curves are extracted using a combined watershed and active contours algorithm and then tiled and converted to a regular surface using a global parameterization algorithm. It is shown that the registration accuracy improves when higher number of salient features (i.e. anatomical point landmarks and surfaces) are used and it also has no impact on the speed of the algorithm. The results show that the target registration error is less than 2 mm and has sub-second performance on intra-subject registration of MR image real datasets. It is observed that the Fast RBF algorithm is relatively insensitive to the increasing number of point landmarks used as compared with the competing feature based algorithms.
机译:医学图像配准是医学图像处理中的基本任务之一。它在图像引导手术(IGS)和计算机辅助诊断(CAD)领域中有多种应用。已经开发出一组非线性方法用于对象间和对象内3D医学图像配准。然而,就准确性和速度而言,有效配准是当今外科手术导航(SN)系统中最需要的一种。本文是一系列实验的结果,这些实验利用快速径向基函数(RBF)技术非刚性地记录一个或多个医学图像。最初,使用组合的分水岭和活动轮廓算法提取一组曲线,然后使用全局参数化算法将其平铺并转换为规则曲面。结果表明,当使用更多数量的显着特征(即解剖点地标和表面)时,配准精度会提高,并且也不会影响算法的速度。结果表明,目标配准误差小于2 mm,并且对MR图像真实数据集的对象内配准具有亚秒级的性能。可以观察到,与基于竞争特征的算法相比,快速RBF算法对使用的点界标数量越来越不敏感。

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