ArticleScientific reports2019
Image quality evaluation in a modern PET system: impact of new reconstructions methods and a radiomics approach.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- An artificial intelligence-driven image quality assessment system for whole-body [European journal of nuclear medicine and molecular imaging · 2023Trial
- Toward an optimized PET reconstruction protocol for spinal cord: superiority of OSEM with TOF and PSF.EJNMMI physics · 2026Article
- The Role of [18F]FDG PET-Based Radiomics and Machine Learning for the Evaluation of Cardiac Sarcoidosis: A Narrative Literature Review.Medicina (Kaunas, Lithuania) · 2025Review
- Impact of tissue-independent positron range correction on [European journal of nuclear medicine and molecular imaging · 2025Article
- Practical use of radiomic features as a metric for image quality discrimination in [EJNMMI reports · 2025Article
- A fully automated, expert-perceptive image quality assessment system for whole-body [18F]FDG PET/CT.EJNMMI research · 2025Article
- Y-90 PET/MR imaging optimization with a Bayesian penalized likelihood reconstruction algorithm.Physical and engineering sciences in medicine · 2024Article
- Automated F18-FDG PET/CT image quality assessment using deep neural networks on a latest 6-ring digital detector system.Scientific reports · 2023Article
- Variability in PET image quality and quantification measured with a permanently filledEJNMMI physics · 2023Article
- Impact of Region-of-Interest Delineation on Stability and Reproducibility of Liver SNR Measurements inWorld journal of nuclear medicine · 2023Article
- Role of Radiomics-Based Baseline PET/CT Imaging in Lymphoma: Diagnosis, Prognosis, and Response Assessment.Molecular imaging and biology · 2022Review
- Effects of Tracer Uptake Time in Non-Small Cell Lung CancerJournal of nuclear medicine : official publication, Society of Nuclear Medicine · 2022Article
- Influences on PET Quantification and Interpretation.Diagnostics (Basel, Switzerland) · 2022Review
- A review on advances inInsights into imaging · 2022Review
- Comparison between Two Different Scanners for the Evaluation of the Role ofJournal of clinical medicine · 2022Article
- Role ofJournal of clinical medicine · 2021Article
- Moving the goalposts while scoring-the dilemma posed by new PET technologies.European journal of nuclear medicine and molecular imaging · 2021Article
- 2-[Cancers · 2021Article
- A Systematic Review of PET Textural Analysis and Radiomics in Cancer.Diagnostics (Basel, Switzerland) · 2021Review
- The Impact of Artificial Intelligence CNN Based Denoising on FDG PET Radiomics.Frontiers in oncology · 2021Article
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5 authors.
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Abstract
The present work investigates the influence of different biological and physical parameters on image quality (IQ) perception of the abdominal area in a modern PET scanner, using new reconstruction algorithms and testing the utility of a radiomics approach. Scans of 112 patients were retrospectively included. Images were reconstructed using both OSEM + PSF and BSRM methods, and IQ of the abdominal region was subjectively evaluated. First, 22 IQ related parameters were obtained (including count rate and biological or mixed parameters) and compared to the subjective IQ scores by means of correlations and logistic regression. Second, an additional set of radiomics features was extracted, and a model was constructed by means of an elastic-net regression. For the OSEM + PSF and especially for the BSRM reconstructions, IQ parameters presented only at best moderated correlations with the subjective IQ. None of the studied parameters presented a good predictive power for IQ, while a simple radiomics model increased the performance of the IQ prediction. These results suggest the necessity of changing the standard parameters to evaluate IQ, particularly when a BSRM algorithm is involved. Furthermore, it seems that a simple radiomics model can outperform the use of any single parameter to assess IQ.
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