Dissertation > Excellent graduate degree dissertation topics show

The big vision cone-beam CT image reconstruction GPU method

Author: ChenDeFeng
Tutor: ZhangPeng
School: Capital Normal University
Course: Applied Computer Technology
Keywords: Cone-beam CT Large field of vision GPU Filtered back projection (BPF)
CLC: TP391.41
Type: Master's thesis
Year: 2008
Downloads: 214
Quote: 3
Read: Download Dissertation


Computed tomography as a nondestructive testing technology has been applied in many fields . Compared with the traditional two-dimensional CT , cone-beam CT ray high utilization , short scan time as well as the direction of the Z-axis resolution of the many advantages to become one of the hot topics of today 's international CT research . Cone-beam CT there are still some problems to limit its application , including imaging small field of view and reconstruction slow . In order to expand the vision cone beam imaging field , with a spiral cone-beam scan mode and bias cone-beam scan mode , were used to expand the the axial vision and lateral vision . In order to improve the reconstruction speed , people using hardware acceleration means , including the use of the FPGA, Cell processors and graphics processors ( GPU ) . Has exceeded the central processor ( CPU ) in the growth rate of the computing capacity of the graphic processor , the floating-point computation capability leading the central processor one to two orders of magnitude . At the same time , the graphics processor programmable function draw high-speed and parallel pipeline and developed in recent years to provide a good running platform for general purpose computing , which makes the GPU - based general-purpose computing research focus attention . Instruction execution mode of the GPU and CPU to GPU-based general-purpose computing must reorganize data structures and algorithm steps , in order to take full advantage of the GPU parallel processing architecture brings the performance advantages . In this paper, the several bias cone-beam scan mode , the use of GPU Computing technology to achieve a wide field cone-beam CT reconstruction algorithm , quickly expanding the horizontal field of view of the cone-beam CT . The algorithm is a BPF type reconstruction algorithm , to avoid the data rearrangement, and therefore does not reduce the image accuracy . Algorithm to optimize the texture is stored , saving memory bandwidth , more suitable for multiple bias the reconstruction of the scan mode , the algorithm runs faster than running on the CPU speed by two orders of magnitude faster .

Related Dissertations

  1. The Clinical Study of Cone-beam CT Combining with Active Breathing Control System on Lung Cancer Radiotherapy,R734.2
  2. Visual Feedback and Memory Behavior Based GPU Parallel Ant Colony Algorithm,TP301.6
  3. Research of Finite Element Method on GPU,O241.82
  4. Research of Image Segmentation in Web Image Search Based on GPUs,TP391.41
  5. GPU-based SIFT algorithm,TP391.41
  6. GPU-based image search Chinese Research on key technologies of the retrieval,TP391.1
  7. Based on GPU / CPU multi- level parallel CFD Optimization Strategy,V221
  8. Ffmpeg-based high-performance high-definition streaming media player software design,TN919.8
  9. Flame effects Augmented Reality System Key Technologies,TP391.9
  10. Efficient multi- GPU based acoustic wave simulator and its application,TP391.41
  11. Research groups and evacuation simulation algorithm simulation system,TP391.9
  12. GPU-accelerated particle filter PET image reconstruction algorithm,TP391.41
  13. GPU-based book recommendation system Research and Implementation,TP391.3
  14. GPU-based acceleration of a linear programming algorithm and its application,TP391.41
  15. GPU-based parallel search algorithm for time series,TP391.41
  16. CPU-based inverse algorithm source strength,TP18
  17. GPU-based reconstruction algorithm for X-rays accelerate research,TP391.41
  18. GPU-based acceleration of neutral gas leak and rescue simulation study,TP391.41
  19. Research on Performance Evaluation and Optimization for CPU-GPU Heterogeneous System,TP306.2
  20. Physically-based Process of Generating and Rendering Technology for High Energy Explosion,TJ510.1
  21. The Three-dimensional Study of Cranifoacial Morphology in Operated Patients with Unilateral Cleft Lip and Palate,R783.5

CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
© 2012 www.DissertationTopic.Net  Mobile