Iterative deblurring for CT metal artifact reduction
- Washington Univ., Saint Louis, MO (United States)
Iterative deblurring methods using the expectation maximization (EM) formulation and the algebraic reconstruction technique (ART), respectively, are adapted for metal artifact reduction in medical computed tomography (CT). In experiments with synthetic noise-free and additive noisy projection data of dental phantoms, it is found that both simultaneous iterative algorithms produce superior image quality as compared to filtered backprojection after linearly fitting projection gaps. Furthermore, the EM-type algorithm converges faster than the ART-type algorithm in terms of either the I-divergence or Euclidean distance between ideal and reprojected data in the simulation. Also, for a given iteration number, the EM-type deblurring method produces better image clarity but stronger noise than the ART-type reconstruction. The computational complexity of EM- and ART-based iterative deblurring is essentially the same, dominated by reprojection and backprojection. Relevant practical and theoretical issues are discussed.
- OSTI ID:
- 418022
- Journal Information:
- IEEE Transactions on Medical Imaging, Journal Name: IEEE Transactions on Medical Imaging Journal Issue: 5 Vol. 15; ISSN 0278-0062; ISSN ITMID4
- Country of Publication:
- United States
- Language:
- English
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