Noise Reduction in Low-Dose Cone Beam CT by Incorporating Prior Volumetric Image Information
Repeated use of cone beam CT (CBCT) in radiotherapy introduces extra imaging dose to patients.In this work,we propose a method to effectively reduce the imaging dose of on-treatment CBCT by incorporating previously acquired CBCT.The Karhunen-Loève (KL) transform was used to consider the correlation among the on-treatment low dose CBCT and prior CBCTs in the projection domain.Following the KL transform,the selected CBCT projection data were decomposed into un-correlated,ordered principle components.Then,a penalized weighted least-squares (PWLS) criterion was applied to restore each KL component using different penalty strengths,where the penalty parameter was inversely proportional to its corresponding KL eigenvalue.Following the inverse KL transform on the processed data,the FDK algorithm was used to reconstruct the on-treatment CBCT image.The proposed algorithm was evaluated using both a CatPhan 600 phantom and an anthropomorphic head phantom.The proposed algorithm demonstrated the ability to suppress noise while preserving edge information effectively.This new strategy outperforms the PWLS algorithm without considering prior information based on the noise-resolution tradeoff measurement and analyze of the reconstructed small objects.Information extracted from previously acquired CBCT can be effectively utilized to suppress noise in on-treatment low-dose CBCT.The presented strategy can significantly lower the patient CBCT radiation dose without compromising the quality of the images.
Low-dose cone beam CT KL transform PWLS principal component analysis prior information
L. Ouyang T. Solberg J. Wang
Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, TX USA
国际会议
World Congress on Medical Physics and Biomedical Engineering (2012年医学物理及生物医学工程国际会议(IFMBE))
北京
英文
1820-1823
2012-05-26（万方平台首次上网日期，不代表论文的发表时间）