基于CUDA的2D、3D刚性配准方法

2D,3D Rigid Registration Algorithm Base on CUDA

目的:实时医学图像配准技术是外科手术导航系统的关键技术之一。在医学图像分析中,图像配准通常是一个非常耗时的操作,不利于临床实时性需求,本文研究实现了图像配准过程的加速。方法:为了提高配准速度,本文提出了一种基于CUDA(compute unified device architecture)编程模型的硬件加速配准新技术,采用并行的方法实现像素的坐标变换,线性插值,同时计算对应像素的灰度值残差。结果:配准误差为亚像素级别,配准速度要比基于CPU的配准快几十甚至上百倍。结论:该方法在保持配准精度不变的前提下,大大提高了刚性配准的速度。

Objective： Real time medical image registration technique is one of the key techniques in image based surgery navigation system. While in medical image analysis, image registration is usually a very time-consuming operation, and this is not conducive to clinical real-time requirements. This paper studies and realizes the acceleration of the process of image registration. Methods： In order to improve the registration rate, in this paper, we propose a new technology which is based on CUDA （Compute Unified Device Architecture） programming model to accelerate the process of registration in hardware, using parallel methods to achieve pixel coordinate transformation, linear interpolation, and calculate the corresponding pixel gray value residuals. Results： The registration is up to the sub-pixel level and the GPU-based registration is dozens or even hundreds of times faster than CPU-based registration. Conclusions： This method greatly enhances the speed of rigid registration without changing the alignment accuracy.