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Content Provider | IEEE Xplore Digital Library |
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Author | Saha, S. Tahtali, M. Lambert, A. Pickering, M. |
Copyright Year | 2013 |
Description | Author affiliation: Sch. of Eng. & Inf. Technol., Univ. of New South Wales, Canberra, NSW, Australia (Saha, S.; Tahtali, M.; Lambert, A.; Pickering, M.) |
Abstract | In this paper, we present an innovative compressive sensing based iterative algorithm for tomographic reconstruction. Back-projection has been customized to make it work even when the projections are not uniformly distributed, and thus ensures a better initial guess to start ART iterations. Contour information of the object has been used efficiently for faster and finer reconstruction. Aiming successful reconstruction with minimum number of iterations, conjugate gradient method that enjoys the full benefit of ART with good initial guess has been used instead of commonly used steepest descent method. Based on the experiments on simulated and real medical images it has been shown that the proposed modality is capable of producing much better reconstruction than the state-of-the-art methods. |
Starting Page | 000398 |
Ending Page | 000403 |
File Size | 1376474 |
Page Count | 6 |
File Format | |
ISBN | 9781479947966 |
DOI | 10.1109/ISSPIT.2013.6781914 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2013-12-12 |
Publisher Place | Greece |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Image reconstruction Australia Biomedical imaging Computed tomography Subspace constraints conjugate gradient compressed sensing iterative approach algebraic reconstruction technique computed tomography |
Content Type | Text |
Resource Type | Article |
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