Fast Implementation of Iterative Reconstruction with Exact Ray-Driven Projector on GPUs  

作　　者：Fang Xu 

机构地区：[1]Siemens Corporate Research, Princeton, NJ 08540, USA

出　　处：《Tsinghua Science and Technology》2010年第1期30-35,共6页清华大学学报（自然科学版（英文版）

摘　　要：Iterative methods are popular choices in image reconstruction fields due to their capability of recovering object information from incomplete acquisition data. However, the computation process involves frequent uses of forward and backward projections that are computationally expensive. Past research has proved that a forward projector that can produce high quality images is crucial to achieve a good convergence rate. In this paper a high performance iterative reconstruction framework is introduced, where two most popular iterative algorithms： Simultaneous Algebraic Reconstruction Technique （SART） and Ordered-subsets Expectation Maximization （OSEM） are supported. The framework utilizes Siddon＇s ray-driven method to generate forward projected images. Benefited from functionalities offered by current generation of graphics processing units （GPUs）, it achieves better performance when compared to previous GPU implementations that use grid-interpolated methods, on top of the significant speedups over CPU-based solutions.Iterative methods are popular choices in image reconstruction fields due to their capability of recovering object information from incomplete acquisition data. However, the computation process involves frequent uses of forward and backward projections that are computationally expensive. Past research has proved that a forward projector that can produce high quality images is crucial to achieve a good convergence rate. In this paper a high performance iterative reconstruction framework is introduced, where two most popular iterative algorithms： Simultaneous Algebraic Reconstruction Technique （SART） and Ordered-subsets Expectation Maximization （OSEM） are supported. The framework utilizes Siddon＇s ray-driven method to generate forward projected images. Benefited from functionalities offered by current generation of graphics processing units （GPUs）, it achieves better performance when compared to previous GPU implementations that use grid-interpolated methods, on top of the significant speedups over CPU-based solutions.

关 键 词：image reconstruction TOMOGRAPHY graphics processing units 

分 类 号：TP334.7[自动化与计算机技术—计算机系统结构] O178[自动化与计算机技术—计算机科学与技术]