ArticleEJNMMI physics2020
Error propagation analysis of seven partial volume correction algorithms for [
Article in EJNMMI physics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- 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
- A cycle-consistent adversarial network for brain PET partial volume correction without prior anatomical information.European journal of nuclear medicine and molecular imaging · 2023Article
- Brain partial volume correction with point spreading function reconstruction in high-resolution digital PET: comparison with an MR-based method in FDG imaging.Annals of nuclear medicine · 2022Article
- DeepPVC: prediction of a partial volume-corrected map for brain positron emission tomography studies via a deep convolutional neural network.EJNMMI physics · 2022Article
- Impact of meningeal uptake and partial volume correction techniques on [Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2022Article
- Regional glucose metabolic decreases with ageing are associated with microstructural white matter changes: a simultaneous PET/MR study.European journal of nuclear medicine and molecular imaging · 2022Article
- CERMEP-IDB-MRXFDG: a database of 37 normal adult human brain [EJNMMI research · 2021Article
- Characterization of point-spread function specification error on Geometric Transfer Matrix partial volume correction in [EJNMMI physics · 2021Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
backgroundNovel partial volume correction (PVC) algorithms have been validated by assuming ideal conditions of image processing; however, in real clinical PET studies, the input datasets include error sources which cause error propagation to the corrected outcome.
methodsWe aimed to evaluate error propagations of seven PVCs algorithms for brain PET imaging with [
resultsUncorrected SUVRs were underestimated against true SUVRs (- 15.7 and - 53.7% in hippocampus for HC and AD conditions), and application of each PVC algorithm reduced the %diff. Larger FWHM mismatch led to larger %diff of PVC-SUVRs against true SUVRs for all algorithms. Inaccurate image registration showed systematic propagation for most algorithms except for SFS-RR and modified SFS-RR. Incorrect segmentation of the anatomical volume only resulted in error propagations in limited local regions.
conclusionsWe demonstrated error propagation by numerical simulation of THK-PET imaging. Error propagations of 7 PVC algorithms for brain PET imaging with [
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