Prior image constrained compressed sensing (PICCS): A method to accurately reconstruct dynamic CT images from highly undersampled projection data sets
University of Wisconsin–Madison
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Abstract
When the number of projections does not satisfy the Shannon/Nyquist sampling requirement, streaking artifacts are inevitable in x-ray computed tomography (CT) images reconstructed using filtered backprojection algorithms. In this letter, the spatial-temporal correlations in dynamic CT imaging have been exploited to sparsify dynamic CT image sequences and the newly proposed compressed sensing (CS) reconstruction method is applied to reconstruct the target image sequences. A prior image reconstructed from the union of interleaved dynamical data sets is utilized to constrain the CS image reconstruction for the individual time frames. This method is referred to as prior image constrained compressed sensing…
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Authors
3Topics & keywords
Topics
Keywords
- Undersampling
- Compressed sensing
- Iterative reconstruction
- Artificial intelligence
- Computer science
- Computer vision
- Projection (relational algebra)
- Sampling (signal processing)
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