Title :
Motion Compensated X-ray CT Algorithm for Moving Objects
Author :
Tanaka, Takumi ; Maeda, Shin-ichi ; Ishii, Shin
Author_Institution :
Grad. Sch. of Inf., Kyoto Univ., Kyoto, Japan
Abstract :
In this study a motion compensated X-ray CT algorithm based on a statistical model is proposed. The important feature of our motion compensated X-ray CT algorithm is that the target object is assumed to move or deform along the time. Then the projections of the deforming target object are described by a state-space model. The deformation is described by motion vectors each attached to each pixel. To reduce the ill-posed ness we incorporate into the prior distribution our a priori knowledge that the target object is composed of a restricted number of materials whose X-ray absorption coefficients are roughly known. To perform Bayesian inference based on our statistical model, the posterior distribution is approximated by a computationally tractable distribution such to minimize Kullback-Leibler (KL) divergence between the posterior and the tractable distributions. Computer simulations using phantom images show the effectiveness of our CT algorithm, suggesting the state-space model works even when the target object is deforming.
Keywords :
X-ray absorption; belief networks; computerised tomography; image motion analysis; inference mechanisms; medical image processing; statistical analysis; Bayesian inference; Kullback-Leibler divergence; X-ray absorption coefficients; computationally tractable distribution; computer simulations; motion compensated X-ray CT algorithm; moving objects; phantom images; posterior distributions; state-space model; statistical model; Absorption; Bayesian methods; Computed tomography; Image reconstruction; Materials; Vectors; X-ray imaging; Bayesian inference; X-ray CT; motion compensation;
Conference_Titel :
Machine Learning and Applications and Workshops (ICMLA), 2011 10th International Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
978-1-4577-2134-2
DOI :
10.1109/ICMLA.2011.97