Self-geometric calibration of circular cone beam CT based on epipolar geometry consistency

Author(s):  
Liang Zheng ◽  
Lujie Chen ◽  
Shuang Luo ◽  
Shouhua Luo
2013 ◽  
Vol 21 (7) ◽  
pp. 1659-1665
Author(s):  
张峰 ZHANG Feng ◽  
江桦 JIANG Hua ◽  
闫镔 YAN Bin ◽  
魏星 WEI Xing ◽  
李磊 LI Lei

2009 ◽  
Vol 2009 ◽  
pp. 1-8 ◽  
Author(s):  
Xing Zhao ◽  
Jing-jing Hu ◽  
Peng Zhang

Currently, 3D cone-beam CT image reconstruction speed is still a severe limitation for clinical application. The computational power of modern graphics processing units (GPUs) has been harnessed to provide impressive acceleration of 3D volume image reconstruction. For extra large data volume exceeding the physical graphic memory of GPU, a straightforward compromise is to divide data volume into blocks. Different from the conventional Octree partition method, a new partition scheme is proposed in this paper. This method divides both projection data and reconstructed image volume into subsets according to geometric symmetries in circular cone-beam projection layout, and a fast reconstruction for large data volume can be implemented by packing the subsets of projection data into the RGBA channels of GPU, performing the reconstruction chunk by chunk and combining the individual results in the end. The method is evaluated by reconstructing 3D images from computer-simulation data and real micro-CT data. Our results indicate that the GPU implementation can maintain original precision and speed up the reconstruction process by 110–120 times for circular cone-beam scan, as compared to traditional CPU implementation.


2017 ◽  
Vol 1 (6) ◽  
pp. 517-526 ◽  
Author(s):  
Jerome Lesaint ◽  
Simon Rit ◽  
Rolf Clackdoyle ◽  
Laurent Desbat

2008 ◽  
Vol 35 (5) ◽  
pp. 2124-2136 ◽  
Author(s):  
M. J. Daly ◽  
J. H. Siewerdsen ◽  
Y. B. Cho ◽  
D. A. Jaffray ◽  
J. C. Irish

Author(s):  
Dufan Wu ◽  
Liang Li ◽  
Li Zhang ◽  
Yuxiang Xing ◽  
Zhiqiang Chen ◽  
...  

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