Fast parallel algorithm for three-dimensional distance-driven model in iterative computed tomography reconstruction

• 作者: 席晓琦 张瀚铭 李建新 李磊 王林元 蔡爱龙 闫镔 陈建林
• 来源期刊: 中国物理B（英文版）
• 关键词: computed tomography iterative reconstruction parallelizable algorithm distance-driven model
• 年，卷（期）: 2015,（2）
• 页码范围: 028703-1-028703-8
• 页数: 1页
• 语种: 英文
• DOI: 10.1088/1674-1056/24/2/028703

摘要

The projection matrix model is used to describe the physical relationship between reconstructed object and projec-tion. Such a model has a strong influence on projection and backprojection, two vital operations in iterative computed tomographic reconstruction. The distance-driven model (DDM) is a state-of-the-art technology that simulates forward and back projections. This model has a low computational complexity and a relatively high spatial resolution; however, it includes only a few methods in a parallel operation with a matched model scheme. This study introduces a fast and par-allelizable algorithm to improve the traditional DDM for computing the parallel projection and backprojection operations. Our proposed model has been implemented on a GPU (graphic processing unit) platform and has achieved satisfactory computational efficiency with no approximation. The runtime for the projection and backprojection operations with our model is approximately 4.5 s and 10.5 s per loop, respectively, with an image size of 256×256×256 and 360 projections with a size of 512×512. We compare several general algorithms that have been proposed for maximizing GPU efficiency by using the unmatched projection/backprojection models in a parallel computation. The imaging resolution is not sacrificed and remains accurate during computed tomographic reconstruction.