一种基于GPU的改进光线投射算法

计算机工程与科学

一种基于GPU的改进光线投射算法

张阿关1,4，蒋慧琴1,4，马岭1,4，杨晓鹏2,4，刘玉敏3,4

（1.郑州大学信息工程学院,河南郑州 450001;2.郑州大学第一附属医院，河南郑州 450001;

3.郑州大学商学院，河南郑州 450001;4.郑州市医疗信息化工程技术研究中心，河南郑州 450001）

收稿日期:2015-09-15 修回日期:2015-12-30 出版日期:2017-01-25 发布日期:2017-01-25
基金资助:
国家自然科学基金（61271146）；河南省科技型中小企业创新资金（132203210030）

An improved ray casting algorithm based on GPU

ZHANG Aguan1,4，JIANG Huiqin1,4，MA Ling1,4，YANG Xiaopeng2,4，LIU Yumin3,4

(1.School of Information Engineering,Zhengzhou University,Zhengzhou 450001;

2.The First Affilicate Hospital of Zhengzhou University,Zhengzhou 450001;

3.Business School,Zhengzhou University,Zhengzhou 450001;

4.Zhengzhou Engineering Technology Research Center for Medical Informatization,Zhengzhou 450001,China)

Received:2015-09-15 Revised:2015-12-30 Online:2017-01-25 Published:2017-01-25

摘要/Abstract

摘要：

针对传统光线投射算法计算量大、速度慢、在没有硬件加速情况下难以实时重建的问题，提出了一种基于GPU编程的快速计算重采样点值的光线投射算法。首先，设计一个GPU程序确定投射光线的终点与方向；其次，采用加速度步长采样方法确定重采样点的位置并利用快速复合插值方法计算重采样点的颜色值；最后，采用不透明度提前截止法进一步加速重建过程。实验结果表明，该方法计算复杂度低、执行效率高。在保证重建图像质量的同时，与现有基于CPU的光线投射算法相比，重建速度提高6倍，与基于GPU的传统光线投射算法相比，速度提高2倍。

关键词: GPU编程, 光线投射, 重采样点, 快速插值, CT图像

Abstract:

Ray casting algorithms can reconstruct 2D tomographic CT images into 3D images, which provide an important means for accurate diagnosis and quantitative analysis of the disease. Because of the large amount of calculation and the slow calculation speed, it is almost impossible for traditional ray casting methods to achieve realtime rendering without hardware acceleration. We propose an improved ray casting algorithm based on GPU. Firstly, we acquire ray ending points and the direction by designing a GPU program. Secondly, we determine the position of resampling points by using the acceleration step sampling method and calculate the values of these points through the fast compound interpolation method. Thirdly, we further accelerate the reconstruction process by using the nontransparency ahead dead method. Experimental results show that the proposed method has the advantages of low complexity and high efficiency. Under the condition of guaranteeing the reconstructed image quality, the rendering speed of the proposed method is 6 times faster than the existing ray casting method based on CPU and 2 times faster than the traditional ray casting algorithm based on GPU. It therefore can provide an effective means for the reconstruction of CT images.

Key words: GPU programming, ray casting, resampling points, fast interpolation, CT images

张阿关1,4，蒋慧琴1,4，马岭1,4，杨晓鹏2,4，刘玉敏3,4. 一种基于GPU的改进光线投射算法[J]. 计算机工程与科学.

ZHANG Aguan1,4，JIANG Huiqin1,4，MA Ling1,4，YANG Xiaopeng2,4，LIU Yumin3,4. An improved ray casting algorithm based on GPU[J]. Computer Engineering & Science.

[1]	王妞妞，安建成. 最佳阈值法结合改进的Freeman链码的肺实质分割[J]. 计算机工程与科学, 2020, 42(06): 1037-1042.
[2]	张海燕1,张立毅1,2，孙云山1,2. 基于离散剪切波正则化的低剂量CT图像统计重建算法[J]. 计算机工程与科学, 2018, 40(01): 86-92.
[3]	刘旭江，徐圆，齐宏亮，洪虹，周凌宏. 基于高斯拉普拉斯的层次剥离体绘制[J]. J4, 2014, 36(06): 1148-1153.
[4]	祖研1，帅仁俊1，陈平2. 基于DICOM标准的医学图像有损压缩的研究[J]. J4, 2011, 33(7): 62-66.
[5]	任小康，白勇峰，范丽，李颜瑞. 基于改进的SVM的甲状腺图像检索[J]. J4, 2011, 33(1): 127-131.
[6]	张翔[2] 张大志[1] 田金文[1] 柳健[1]. 基于相关性的快速体绘制研究[J]. J4, 2005, 27(2): 33-35.
[7]	周璐[1] 乐嘉陵[2]. 计算流动显示——概念,原理及实现[J]. J4, 2000, 22(1): 7-9.