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Dynamic positron emission tomography restoration with low-rank representation incorporating edge preservation.
- Source :
-
Journal of X-Ray Science & Technology . 2016, Vol. 24 Issue 5, p709-722. 14p. 4 Color Photographs, 1 Black and White Photograph, 1 Diagram, 1 Chart, 5 Graphs. - Publication Year :
- 2016
-
Abstract
- BACKGROUND: Dynamic positron emission tomography (PET) is a powerful tool that provides useful quantitative information on physiological and biochemical processes. However, the low signal-to-noise ratio (SNR) in short dynamic frames is a challenge. OBJECTIVE: To get high SNR in the dynamic PET and to achieve high-quality PET parametric image are the objective of this study. METHODS: Low-rank (LR) modeling and edge-preserving prior are incorporated in this study with a unified mathematical framework to improve the SNR of a dynamic PET image series. The proposed algorithm is designed to reduce noise in homogeneous areas while preserving the edges of regions of interest. RESULTS: The performance of the proposed method (LRH) is compared both visually and quantitatively by using the classic Gaussian filter and an LR expression filter on a digital brain phantom and in vivo rat study. Experimental results demonstrate that the proposed filter can achieve superior visual and quantitative performance without sacrificing spatial resolution. CONCLUSIONS: The proposed LRH is considerably effective and exhibits great potential in processing dynamic PET data with high noise levels. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 08953996
- Volume :
- 24
- Issue :
- 5
- Database :
- Academic Search Index
- Journal :
- Journal of X-Ray Science & Technology
- Publication Type :
- Academic Journal
- Accession number :
- 118679360
- Full Text :
- https://doi.org/10.3233/XST-160582