DocumentCode :
2376007
Title :
Simultaneous reconstruction and registration algorithm for limited view transmission tomography using a multiple cluster approximation to the joint histogram with an anatomical prior
Author :
Van de Sompel, Dominique ; Brady, Michael
Author_Institution :
Dept. of Eng. Sci., Univ. of Oxford, Oxford, UK
fYear :
2009
fDate :
3-6 Sept. 2009
Firstpage :
5733
Lastpage :
5736
Abstract :
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.
Keywords :
biomedical optical imaging; image reconstruction; image registration; medical image processing; optical tomography; Bayesian probability theory; bivariate clusters; data insufficiency problem; image reconstruction; image registration; joint histogram; limited view transmission tomography; multimodal anatomical priors; multiple cluster approximation; similarity metric; Algorithms; Artificial Intelligence; Cluster Analysis; Image Enhancement; Image Interpretation, Computer-Assisted; Pattern Recognition, Automated; Phantoms, Imaging; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted; Subtraction Technique; Tomography, X-Ray;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE
Conference_Location :
Minneapolis, MN
ISSN :
1557-170X
Print_ISBN :
978-1-4244-3296-7
Electronic_ISBN :
1557-170X
Type :
conf
DOI :
10.1109/IEMBS.2009.5332591
Filename :
5332591
Link To Document :
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