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학술지 Sparse-View CT Image Recovery Using Two-Step Iterative Shrinkage-Thresholding Algorithm
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저자
채병규, 이수열
발행일
201512
출처
ETRI Journal, v.37 no.6, pp.1251-1258
ISSN
1225-6463
출판사
한국전자통신연구원 (ETRI)
DOI
https://dx.doi.org/10.4218/etrij.15.0115.0401
초록
We investigate an image recovery method for sparseview computed tomography (CT) using an iterative shrinkage algorithm based on a second-order approach. The two-step iterative shrinkage-thresholding (TwIST) algorithm including a total variation regularization technique is elucidated to be more robust than other firstorder methods; it enables a perfect restoration of an original image even if given only a few projection views of a parallel-beam geometry. We find that the incoherency of a projection system matrix in CT geometry sufficiently satisfies the exact reconstruction principle even when the matrix itself has a large condition number. Image reconstruction from fan-beam CT can be well carried out, but the retrieval performance is very low when compared to a parallel-beam geometry. This is considered to be due to the matrix complexity of the projection geometry. We also evaluate the image retrieval performance of the TwIST algorithm using measured projection data.
키워드
Compressed sensing, Projection system matrix, Sparse-view CT image reconstruction, Total variation regularization, TwIST algorithm
KSP 제안 키워드
CT image reconstruction, Compressed sensing, Computed tomography(C.T), Condition number, Exact reconstruction, Image recovery, Image retrieval, Parallel-Beam, Projection System, Recovery method, Regularization technique