Globally convergent 3D dynamic PET reconstruction with patch-based non-convex low rank regularization

Kim, K. S.; Son, Young-Don; Cho, Z. H.; B., J.; Ye, J. C.

doi:10.1109/isbi.2013.6556685

Cited by 3 publications

(2 citation statements)

References 7 publications

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“…Here, a low rank constraint is originated from the matrix completion problem in compressed sensing [4]. Specifically, in this paper, a non-convex low rank regularization is exploited [5]. To deal with this issue, the concave-convex procedure (CCCP) [6] is used to convexify the concave rank prior.…”

Section: Introductionmentioning

confidence: 99%

ECG-gated cardiac CT reconstruction using patch based low rank regularization

Kim

2014

2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI)

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Cardiac computed tomography (CT) is widely used in diagnosis for the coronary artery heart disease. Due to the heart motion, ECG gating is usually applied to the cardiac CT. Although diastolic phase has mostly enough angular data, the systolic phase suffers from insufficient angular data. Hence, the main goal of this paper is to develop a patch based low rank regularization approach that exploits inherent similarities between diastolic and systolic images for reducing artifacts in systolic image. In particular, our optimization framework is based on the Poisson log-likelihood and the non-convex low rank regularization. To address the nonseparable and non-convex optimization problem, we used the separable paraboloidal surrogates (SPS) for Poisson loglikelihood, and the concave-convex procedure (CCCP) for non-convex low rank regularization, which guarantees the fast convergence. We confirm that the proposed algorithm can provide significantly improved image quality.

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Section: Introductionmentioning

confidence: 99%

ECG-gated cardiac CT reconstruction using patch based low rank regularization

Kim

2014

2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI)

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“…of Bio and Brain Engineering, KAIST, 291 Daehak-ro, Yuseong-gu, Daejon 305-701, Republic of Korea the matrix completion problem in compressed sensing [4]. Specifically, a non-convex low rank regularization has been exploited [5]. To deal with this issue, the concave-convex procedure (CCCP) [6] is used to convexify the concave rank prior.…”

Section: Introductionmentioning

confidence: 99%

Low-dose limited view 4D CT reconstruction using patch-based low-rank regularization

Kim

2013

2013 IEEE Nuclear Science Symposium and Medical Imaging Conference (2013 NSS/MIC)

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Dynamic 4D x-ray computed tomography (CT) is often used for several applications such as respiratory and cardiac imaging. To acquire enough data for several phases, repeated xray CT scans should be conducted. Thus, the dose reduction is one of important issues for dynamic CT scans. Another issue is that insufficient angular sampling can be occurred by fast motions such as a cardiac CT imaging. In this paper, the main goal is to develop a patch based low rank regularization approach that exploits inherent similarities between dynamic images for reducing both noise and motion artifacts incurred by low dose and insufficient angular sampling, respectively. In particular, our optimization framework is based on the Poisson log-likelihood and the non-convex low rank regularization. To address the non-separable and non-convex optimization problem, we used the separable paraboloidal surrogates (SPS) for Poisson log-likelihood, and the concave-convex procedure (CCCP) for non-convex low rank regularization, which guarantees the fast convergence. We confirm that the proposed algorithm can provide significantly improved image quality.

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Enhancement of dynamic myocardial perfusion PET images based on low-rank plus sparse decomposition

Mohy-ud-Din

et al. 2018

Computer Methods and Programs in Biomedicine

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Globally convergent 3D dynamic PET reconstruction with patch-based non-convex low rank regularization

Cited by 3 publications

References 7 publications

ECG-gated cardiac CT reconstruction using patch based low rank regularization

ECG-gated cardiac CT reconstruction using patch based low rank regularization

Low-dose limited view 4D CT reconstruction using patch-based low-rank regularization

Enhancement of dynamic myocardial perfusion PET images based on low-rank plus sparse decomposition

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