2016
DOI: 10.1118/1.4960365
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A phantom design for assessment of detectability in PET imaging

Abstract: This phantom provides a practical method for testing and comparison of lesion detectability as a function of imaging system, acquisition parameters, and image reconstruction methods and parameters.

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Cited by 22 publications
(29 citation statements)
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“…(I) PET phantom, ( II ) 3D printed lesions . Figure license: Wollenweber, et al #bib2016, A phantom design for assessment of detectability in PET imaging.…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…(I) PET phantom, ( II ) 3D printed lesions . Figure license: Wollenweber, et al #bib2016, A phantom design for assessment of detectability in PET imaging.…”
Section: Resultsmentioning
confidence: 99%
“…However, this new field has great potential to achieve more versatile phantoms. 10,[16][17][18][19][20][21]24,32,42,52,59,69,72,75,76,80…”
Section: B Characterization Of Phantom Imaging Valuesmentioning
confidence: 99%
“…From the reported heterogeneous phantom inserts, it was observed that most of the approaches present thick walls, which is not the case in real patient tumors. Considering this factor, the wall-less models proposed by Carles et al 42 and Wollenweber et al 49 are good examples of a more realistic tumor heterogeneity simulation. One aim of having reference objects for specific imaging applications is their usability across systems and centers, allowing the testing and validation of different imaging methods prior to being applied in patient studies.…”
Section: Summary and Discussionmentioning
confidence: 99%
“…48 In another study, Wollenweber et al present a phantom design for assessing lesion detectability in PET. 49 The phantom includes hollow 3D printed dodecahedral nylon inserts and a heterogeneous background composed of acrylic spheres. The components are embedded in a plastic cylinder compartment filled with [18F]FDG and one drop of detergent as a surfactant.…”
Section: A 3d Printed Pet(/ct) Imaging Phantomsmentioning
confidence: 99%
“…non-homogenous, asymmetric structures, variability in structure size, orientation, shape). Patient images, conversely, rarely have reliable ground truths associated with them [2], [3], against which image derived metrics can be compared. Deriving ground truth information from the images themselves is conceptually flawed, especially for faint structures around the spatial resolution of the system, but comparison between alternative image generating techniques may be appropriate as demonstrated in Figure 3, where changes in reconstruction parameters lead to varying lesion conspicuousness.…”
Section: Chapter 1: Introductionmentioning
confidence: 99%