Simultaneous reconstruction and registration algorithm for limited view transmission tomography using a multiple cluster approximation to the joint histogram with an anatomical prior.
We develop a novel simultaneous reconstruction and registration algorithm for limited view transmission tomography. We derive a cost function using Bayesian probability theory, and propose a similarity metric based on the explicit modeling of the joint histogram as a sum of bivariate clusters. The resulting algorithm shows a robust mitigation of the data insufficiency problem in limited view tomography. To our knowledge, our work represents the first attempt to incorporate non-registered, multimodal anatomical priors into limited view transmission tomography by using joint histogram based similarity measures.
Van de Sompel
Dominique
D
Department of Engineering Science, University of Oxford, Oxford, UK. dominique@robots.ox.ac.uk
Brady
Michael
M
D000465:Algorithms; D001185:Artificial Intelligence; D016000:Cluster Analysis; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D019047:Phantoms, Imaging; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D013382:Subtraction Technique; D014056:Tomography, X-Ray / Q000379:methods*