Image Reconstruction of Sparse Fan-beam Projections Using a Hybrid Algorithm

摘要：

Image reconstruction from sparse fan-beam projection data would result in image error. In this paper, a hybrid imaging algorithm from sparse fan-beam projections is proposed. The first, high exact sparse spectrum data is extracted from image reconstruction from sparse fan-beam projections by filtered backprojection (FBP), and then image is reconstructed from the data using the iterative next-neighbor regridding (INNG) algorithm combined with total variation (TV) gradient descent method. The INNG step can restrict image distortions around the model and the TV gradient descent step can remove small oscillations in the model while preserving edges. The combined method is compared with the original INNG algorithm and TV gradient descent method. Computer simulation results demonstrate that the hybrid algorithm is effective for sparse fan-beam projection reconstruction.

关键词： reconstruction Fan-beam projection Sparse INNG total variation

作者: Moyan Xiao Jianhua Luo

作者单位: Department of Biomedical Engineering Shanghai Jiao Tong University Shanghai, China

会议类型: 国际会议

会议名称: 2011 International Conference on Electronics and Optoelectronics(2011电子学与光电子学国际会议 ICEOE 2011)

会议地点: 大连

会议语种:英文

页码: 43-46

在线出版日期: 2011-07-29（万方平台首次上网日期，不代表论文的发表时间）