ArticleMedical image analysis2018
Joint solution for PET image segmentation, denoising, and partial volume correction.
Article in Medical image analysis, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Advances and Challenges in Pharmacokinetic Modeling for PET Imaging: Compartment Models, Input Functions, and Quantitative Techniques.Tomography (Ann Arbor, Mich.) · 2026Review
- Critical review of partial volume correction methods in PET and SPECT imaging: benefits, pitfalls, challenges, and future outlook.European journal of nuclear medicine and molecular imaging · 2026Review
- Automated segmentation of the primary tumor in nasopharyngeal carcinoma using a deep learning framework in positron emission tomography imaging: a comparative study.Quantitative imaging in medicine and surgery · 2025Article
- A narrative review of imaging intratumor heterogeneity in non-small cell lung cancer: current advances.Translational lung cancer research · 2025Review
- Elucidation of FDG-PET Imaging Characteristics that Reflect the Heterogeneity within Tumors Due to Variability in Metabolic Activity: A Phantom Study.World journal of nuclear medicine · 2025Article
- Deep learning-based partial volume correction in standard and low-dose positron emission tomography-computed tomography imaging.Quantitative imaging in medicine and surgery · 2024Article
- Segmentation of Dynamic Total-Body [International journal of biomedical imaging · 2023Article
- Musculoskeletal MR Image Segmentation with Artificial Intelligence.Advances in clinical radiology · 2022Article
- Computational approaches to detect small lesions inJournal of applied clinical medical physics · 2021Article
- Voxel-based partial volume correction of PET images via subtle MRI guided non-local means regularization.Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) · 2021Article
- Deep learning-assisted ultra-fast/low-dose whole-body PET/CT imaging.European journal of nuclear medicine and molecular imaging · 2021Article
- Non-local mean denoising using multiple PET reconstructions.Annals of nuclear medicine · 2021Article
- Design and evaluation of an accurate CNR-guided small region iterative restoration-based tumor segmentation scheme for PET using both simulated and real heterogeneous tumors.Medical & biological engineering & computing · 2020Article
- A new development of non-local image denoising using fixed-point iteration for non-convex ℓp sparse optimization.PloS one · 2018Article
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Authors and funding
7 authors.
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Abstract
Segmentation, denoising, and partial volume correction (PVC) are three major processes in the quantification of uptake regions in post-reconstruction PET images. These problems are conventionally addressed by independent steps. In this study, we hypothesize that these three processes are dependent; therefore, jointly solving them can provide optimal support for quantification of the PET images. To achieve this, we utilize interactions among these processes when designing solutions for each challenge. We also demonstrate that segmentation can help in denoising and PVC by locally constraining the smoothness and correction criteria. For denoising, we adapt generalized Anscombe transformation to Gaussianize the multiplicative noise followed by a new adaptive smoothing algorithm called regional mean denoising. For PVC, we propose a volume consistency-based iterative voxel-based correction algorithm in which denoised and delineated PET images guide the correction process during each iteration precisely. For PET image segmentation, we use affinity propagation (AP)-based iterative clustering method that helps the integration of PVC and denoising algorithms into the delineation process. Qualitative and quantitative results, obtained from phantoms, clinical, and pre-clinical data, show that the proposed framework provides an improved and joint solution for segmentation, denoising, and partial volume correction.
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