Regularized iterative weighted filtered backprojection for helical cone-beam CT

2008 ◽  
Vol 35 (9) ◽  
pp. 4173-4185 ◽  
Author(s):  
Johan Sunnegårdh ◽  
Per-Erik Danielsson
Keyword(s):  
Cone Beam Ct ◽  
Cone Beam ◽  
Filtered Backprojection

scholarly journals Parallel Implementation of Katsevich's FBP Algorithm

2006 ◽  
Vol 2006 ◽  
pp. 1-8 ◽  
Author(s):  
Jiansheng Yang ◽  
Xiaohu Guo ◽  
Qiang Kong ◽  
Tie Zhou ◽  
Ming Jiang
Keyword(s):  
Numerical Experiments ◽  
Parallel Implementation ◽  
Cone Beam Ct ◽  
Computation Time ◽  
Cone Beam ◽  
Filtered Backprojection ◽  
Typical Experiment ◽  
Linux Cluster ◽  
Parallel Reconstruction ◽  
Reconstruction Time

For spiral cone-beam CT, parallel computing is an effective approach to resolving the problem of heavy computation burden. It is well known that the major computation time is spent in the backprojection step for either filtered-backprojection (FBP) or backprojected-filtration (BPF) algorithms. By the cone-beam cover method [1], the backprojection procedure is driven by cone-beam projections, and every cone-beam projection can be backprojected independently. Basing on this fact, we develop a parallel implementation of Katsevich's FBP algorithm. We do all the numerical experiments on a Linux cluster. In one typical experiment, the sequential reconstruction time is 781.3 seconds, while the parallel reconstruction time is 25.7 seconds with 32 processors.

scholarly journals Exact Interior Reconstruction with Cone-Beam CT

2007 ◽  
Vol 2007 ◽  
pp. 1-5 ◽  
Author(s):  
Yangbo Ye ◽  
Hengyong Yu ◽  
Ge Wang
Keyword(s):  
Singular Value Decomposition ◽  
Convex Set ◽  
Cone Beam Ct ◽  
Singular Value ◽  
Cone Beam ◽  
Filtered Backprojection ◽  
Volume Of Interest ◽  
Interior Problem ◽  
Value Decomposition ◽  
Svd Method

Using the backprojection filtration (BPF) and filtered backprojection (FBP) approaches, respectively, we prove that with cone-beam CT the interior problem can be exactly solved by analytic continuation. The prior knowledge we assume is that a volume of interest (VOI) in an object to be reconstructed is known in a subregion of the VOI. Our derivations are based on the so-called generalized PI-segment (chord). The available projection onto convex set (POCS) algorithm and singular value decomposition (SVD) method can be applied to perform the exact interior reconstruction. These results have many implications in the CT field and can be extended to other tomographic modalities, such as SPECT/PET, MRI.

scholarly journals A Filtered Backprojection Algorithm for Triple-Source Helical Cone-Beam CT

2009 ◽  
Vol 28 (3) ◽  
pp. 384-393 ◽  
Author(s):  
Jun Zhao ◽  
Yannan Jin ◽  
Yang Lu ◽  
Ge Wang
Keyword(s):  
Cone Beam Ct ◽  
Cone Beam ◽  
Filtered Backprojection
Sign in / Sign up

Export Citation Format

Share Document