Implementation and evaluation of various demons deformable image registration algorithms on a GPU

被引:197
作者
Gu, Xuejun [1 ]
Pan, Hubert [1 ]
Liang, Yun [1 ]
Castillo, Richard [2 ]
Yang, Deshan [3 ]
Choi, Dongju [4 ]
Castillo, Edward [5 ]
Majumdar, Amitava [4 ]
Guerrero, Thomas [5 ]
Jiang, Steve B. [1 ]
机构
[1] Univ Calif San Diego, Dept Radiat Oncol, La Jolla, CA 92037 USA
[2] Univ Texas MD Anderson Canc Ctr, Dept Imaging Phys, Houston, TX 77030 USA
[3] Washington Univ, Dept Radiat Oncol, Sch Med, St Louis, MO 63110 USA
[4] Univ Calif San Diego, San Diego Supercomp Ctr, La Jolla, CA 92093 USA
[5] Univ Texas MD Anderson Canc Ctr, Dept Radiat Oncol, Houston, TX 77030 USA
关键词
ADAPTIVE RADIATION-THERAPY; PLAN MODIFICATION; DOSE CALCULATION; RE-OPTIMIZATION; IMRT; RECONSTRUCTION; VALIDATION;
D O I
10.1088/0031-9155/55/1/012
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Online adaptive radiation therapy (ART) promises the ability to deliver an optimal treatment in response to daily patient anatomic variation. A major technical barrier for the clinical implementation of online ART is the requirement of rapid image segmentation. Deformable image registration (DIR) has been used as an automated segmentation method to transfer tumor/organ contours from the planning image to daily images. However, the current computational time of DIR is insufficient for online ART. In this work, this issue is addressed by using computer graphics processing units (GPUs). A gray-scale-based DIR algorithm called demons and five of its variants were implemented on GPUs using the compute unified device architecture (CUDA) programming environment. The spatial accuracy of these algorithms was evaluated over five sets of pulmonary 4D CT images with an average size of 256 x 256 x 100 and more than 1100 expert-determined landmark point pairs each. For all the testing scenarios presented in this paper, the GPU-based DIR computation required around 7 to 11 s to yield an average 3D error ranging from 1.5 to 1.8 mm. It is interesting to find out that the original passive force demons algorithms outperform subsequently proposed variants based on the combination of accuracy, efficiency and ease of implementation.
引用
收藏
页码:207 / 219
页数:13
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