ArticleEJNMMI physics2023
Impact of γ factor in the penalty function of Bayesian penalized likelihood reconstruction (Q.Clear) to achieve high-resolution PET images.
Article in EJNMMI physics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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19 citing papers in PubMed.
- Straightforward PET phantom preparation usingAnnals of nuclear medicine · 2026Article
- Characterization of open-source BSREM reconstruction forPhysical and engineering sciences in medicine · 2026Article
- Reconstruction-dependent differences in brain [18F]FDG PET: a large-scale same-acquisition comparison of Q.Clear and VUE Point FX.Annals of nuclear medicine · 2026Article
- PET Image Reconstruction Using Deep Diffusion Image Prior.IEEE transactions on medical imaging · 2026Article
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- A comparison of three-dimensional-ring CZT and NaI(Tl) single-photon emission computed tomography systems usingQuantitative imaging in medicine and surgery · 2026Article
- Does Q.Clear Processing Change PET Ratios? Quantitative Evidence Using BTXBrain-DAT.Brain sciences · 2025Article
- Innovations in clinical PET image reconstruction: advances in Bayesian penalized likelihood algorithm and deep learning.Annals of nuclear medicine · 2025Review
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- Effects of a deep learning-based image quality enhancement method on a digital-BGO PET/CT system forEJNMMI physics · 2025Article
- Optimization of penalization function in Bayesian penalized likelihood reconstruction algorithm for [Physical and engineering sciences in medicine · 2024Article
- 360° CZT-SPECT/CT cameras:EJNMMI physics · 2024Article
- β1600 Q.Clear Digital Reconstruction of [Journal of clinical medicine · 2024Article
- Impact of [Annals of nuclear medicine · 2024Article
- Phantom and clinical evaluation of the Bayesian penalised likelihood reconstruction algorithm Q.Clear without PSF correction in amyloid PET images.EJNMMI physics · 2024Article
- Investigation of PET image quality with acquisition time/bed and enhancement of lesion quantification accuracy through deep progressive learning.EJNMMI physics · 2024Article
- The effects of various penalty parameter values in Q.Clear algorithm for rectal cancer detection onEJNMMI physics · 2023Article
- Phantom and clinical evaluation of Block Sequential Regularized Expectation Maximization (BSREM) reconstruction algorithm in 68Ga-PSMA PET-CT studies.Physical and engineering sciences in medicine · 2023Article
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Abstract
backgroundThe Bayesian penalized likelihood PET reconstruction (BPL) algorithm, Q.Clear (GE Healthcare), has recently been clinically applied to clinical image reconstruction. The BPL includes a relative difference penalty (RDP) as a penalty function. The β value that controls the behavior of RDP determines the global strength of noise suppression, whereas the γ factor in RDP controls the degree of edge preservation. The present study aimed to assess the effects of various γ factors in RDP on the ability to detect sub-centimeter lesions.
methodsAll PET data were acquired for 10 min using a Discovery MI PET/CT system (GE Healthcare). We used a NEMA IEC body phantom containing spheres with inner diameters of 10, 13, 17, 22, 28 and 37 mm and 4.0, 5.0, 6.2, 7.9, 10 and 13 mm. The target-to-background ratio of the phantom was 4:1, and the background activity concentration was 5.3 kBq/mL. We also evaluated cold spheres containing only non-radioactive water with the same background activity concentration. All images were reconstructed using BPL + time of flight (TOF). The ranges of β values and γ factors in BPL were 50-600 and 2-20, respectively. We reconstructed PET images using the Duetto toolbox for MATLAB software. We calculated the % hot contrast recovery coefficient (CRC
resultsThe CRC
conclusionHigh and low γ factors, respectively, preserved the edges of reconstructed PET images and promoted image smoothing. The BPL with a γ factor above the default value in Q.Clear (γ factor = 2) generated high-resolution PET images, although image noise slightly diverged. Optimizing the β value and the γ factor in BPL enabled the detection of lesions ≤ 6.2 mm.
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