Paper Info
Title
EM+TV based reconstruction for cone-beam CT with reduced radiation
Abstract
Computerized tomography (CT) plays a critical role in modern medicine. However, the radiation associated with CT is significant. Methods that can enable CT imaging with less radiation exposure but without sacrificing image quality are therefore extremely important. This paper introduces a novel method for enabling image reconstruction at lower radiation exposure levels with convergence analysis. The method is based on the combination of expectation maximization (EM) and total variation (TV) regularization. While both EM and TV methods are known, their combination as described here is novel. We show that EM+TV can reconstruct a better image using much fewer views, thus reducing the overall dose of radiation. Numerical results show the efficiency of the EM+TV method in comparison to filtered backprojection and classic EM. In addition, the EM+TV algorithm is accelerated with GPU multicore technology, and the high performance speed-up makes the EM+TV algorithm feasible for future practical CT systems.
Year
DOI
Venue
2011
10.1007/978-3-642-24028-7_1
ISVC (1)
Keywords
Field
DocType
radiation exposure,tv algorithm,future practical ct system,image quality,enabling image reconstruction,reduced radiation,ct imaging,better image,tv method,cone-beam ct,lower radiation exposure level,classic em,expectation maximization,total variation
Iterative reconstruction,Convergence (routing),Computer vision,Computer science,Expectation–maximization algorithm,Image quality,Tomography,Regularization (mathematics),Beam (structure),Artificial intelligence,Radiation
Conference
Citations 
PageRank 
References 
1
0.44
1
Authors
6
Name
Order
Citations
PageRank
Ming Yan126917.69
Jian-Wen Chen27715.80
Luminita A. Vese35389302.64
John Villasenor4641114.37
Alex Bui531848.20
Jason Cong67069515.06