Dynamic 3D PET reconstruction for kinetic analysis using patch-based low-rank penalty
- Authors
- Kim, K.S.; Son, Y.D.; Cho, Z.H.; Ra, J.B.; Ye, J.C.
- Issue Date
- Nov-2012
- Publisher
- IEEE
- Citation
- IEEE Nuclear Science Symposium Conference Record, pp.3430 - 3433
- Journal Title
- IEEE Nuclear Science Symposium Conference Record
- Start Page
- 3430
- End Page
- 3433
- URI
- https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/17507
- DOI
- 10.1109/NSSMIC.2012.6551782
- ISSN
- 1095-7863
- Abstract
- Dynamic positron emission tomography (PET) is widely used to identify metabolism over time. However, conventional reconstruction algorithm provides a noisy reconstruction due to the lack of photon counts in each frame. Therefore, the main goal of this paper is to develop a novel spatio-temporal regularization approach that exploits inherent similarities within intra- and inter- frames. One of the main contributions of this paper is to demonstrate that such correlations can be exploited using a low rank constraint of overlapping similarity blocks. The resulting optimization framework is, however, non-smooth and non Lipschitz due to the low-rank penalty terms and Poisson log-likelihood. Therefore, we propose a novel globally convergent optimization method using the concave-convex procedure (CCCP) by exploiting Legendre-Fenchel transform. We confirm that the proposed algorithm can provide significantly improved image quality. © 2012 IEEE.
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