Compressed sensing-based image reconstruction for discrete tomography with sparse view and limited angle geometries.
This paper addresses the image reconstruction problem in discrete tomography, particularly under challenging imaging conditions such as sparse-view and limited-angle geometries commonly encountered in computed tomography (CT). These conditions often result in low-quality reconstructions due to insuf...
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Main Authors: | , , |
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Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2025-01-01
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Series: | PLoS ONE |
Online Access: | https://doi.org/10.1371/journal.pone.0327666 |
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