title: An Effective CUDA Parallelization of Projection in Iterative Tomography Reconstruction.
abstract: Projection and back-projection are the most computationally intensive parts in Computed Tomography (CT) reconstruction, and are essential to acceleration of CT reconstruction algorithms. Compared to back-projection, parallelization efficiency in projection is highly limited by racing condition and thread unsynchronization. In this paper, a strategy of Fixed Sampling Number Projection (FSNP) is proposed to ensure the operation synchronization in the ray-driven projection with Graphical Processing Unit (GPU). Texture fetching is also used utilized to further accelerate the interpolations in both projection and back-projection. We validate the performance of this FSNP approach using both simulated and real cone-beam CT data. Experimental results show that compare to the conventional approach, the proposed FSNP method together with texture fetching is 10~16 times faster than the conventional approach based on global memory, and thus leads to more efficient iterative algorithm in CT reconstruction.
authors.affiliation: Oral Hospital of Jiangsu Province, Affiliated to Nanjing Medical University, Jiangsu, China.
authors.forename: Lizhe
authors.initials: L
authors.lastname: Xie
authors.affiliation: Centre de Recherche en Information Biomedicale Sino-Francais (LIA CRIBs), Rennes, France.|The Laboratory of Image Science and Technology, Southeast University, Nanjing, China.|The Key Laboratory of Computer Network and Information Integration (Southeast University), Ministry of Education, Beijing, China.
authors.forename: Yining
authors.initials: Y
authors.lastname: Hu
authors.affiliation: Oral Hospital of Jiangsu Province, Affiliated to Nanjing Medical University, Jiangsu, China.
authors.forename: Bin
authors.initials: B
authors.lastname: Yan
authors.affiliation: Oral Hospital of Jiangsu Province, Affiliated to Nanjing Medical University, Jiangsu, China.
authors.forename: Lin
authors.initials: L
authors.lastname: Wang
authors.affiliation: Department of Radiology, General Hospital of Shenyang Military Area Command, Shenhe District, Shenyang, China.
authors.forename: Benqiang
authors.initials: B
authors.lastname: Yang
authors.affiliation: Department of Radiology, General Hospital of Shenyang Military Area Command, Shenhe District, Shenyang, China.
authors.forename: Wenyuan
authors.initials: W
authors.lastname: Liu
authors.affiliation: Department of Radiology, General Hospital of Shenyang Military Area Command, Shenhe District, Shenyang, China.
authors.forename: Libo
authors.initials: L
authors.lastname: Zhang
authors.affiliation: Centre de Recherche en Information Biomedicale Sino-Francais (LIA CRIBs), Rennes, France.|The Laboratory of Image Science and Technology, Southeast University, Nanjing, China.|The Key Laboratory of Computer Network and Information Integration (Southeast University), Ministry of Education, Beijing, China.
authors.forename: Limin
authors.initials: L
authors.lastname: Luo
authors.affiliation: Centre de Recherche en Information Biomedicale Sino-Francais (LIA CRIBs), Rennes, France.|The Laboratory of Image Science and Technology, Southeast University, Nanjing, China.|The Key Laboratory of Computer Network and Information Integration (Southeast University), Ministry of Education, Beijing, China.
authors.forename: Huazhong
authors.initials: H
authors.lastname: Shu
authors.affiliation: Centre de Recherche en Information Biomedicale Sino-Francais (LIA CRIBs), Rennes, France.|The Laboratory of Image Science and Technology, Southeast University, Nanjing, China.|The Key Laboratory of Computer Network and Information Integration (Southeast University), Ministry of Education, Beijing, China.
authors.forename: Yang
authors.initials: Y
authors.lastname: Chen
mesh_terms: D000465:Algorithms; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D014057:Tomography, X-Ray Computed / Q000379:methods*