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An Automated and High Precision Quantitative Analysis of the ACR Phantom

Title: An Automated and High Precision Quantitative Analysis of the ACR Phantom
Authors: Markiewicz, PJ; Da Costa-Luis, C; Dickson, J; Barnes, A; Krokos, G; MacKewn, J; Clark, T; Wimberley, C; MacNaught, G; Yaqub, MM; Gispert, JD; Hutton, BF; Marsden, P; Hammers, A; Reader, AJ; Ourselin, S; Herholz, K; Matthews, JC; Barkhof, F
Source: In: 2021 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC). IEEE: Piscataway, NJ, USA. (2022)
Publisher Information: IEEE
Publication Year: 2022
Collection: University College London: UCL Discovery
Subject Terms: Image registration; Uncertainty; Image resolution; Statistical analysis,Image edge detection; Phantoms; Radiology
Description: A novel phantom-imaging platform for automated and high precision imaging of the American College of Radiology (ACR) PET phantom is proposed. The platform facilitates the generation of an accurate μ-map for PET/MR systems with a robust alignment based on two-stage image registration using specifically designed PET templates. The automated analysis of PET images uses a set of granular composite volume of interest (VOI) templates in a 0.5 mm resolution grid for sampling of the system response to the insert step functions. The impact of the activity outside the field of view (FOV) was evaluated using two acquisitions of 30 minutes each, with and without the activity outside the FOV. Iterative image reconstruction was employed with and without modelled shift-invariant point spread function (PSF) and varying ordered subsets expectation maximisation (OSEM) iterations. Uncertainty analysis of all image-derived statistics was performed using bootstrap resampling of the list-mode data. We found that the activity outside the FOV can adversely affect the imaging planes close to the edge of the axial FOV, reducing the contrast, background uniformity and overall quantitative accuracy. The PSF had a positive impact on contrast recovery (although it slows convergence). The proposed platform may be helpful in a more informative evaluation of PET systems and image reconstruction methods.
Document Type: report
File Description: text
Language: English
Relation: https://discovery.ucl.ac.uk/id/eprint/10187344/1/2022145880.pdf; https://discovery.ucl.ac.uk/id/eprint/10187344/
Availability: https://discovery.ucl.ac.uk/id/eprint/10187344/1/2022145880.pdf; https://discovery.ucl.ac.uk/id/eprint/10187344/
Rights: open
Accession Number: edsbas.5961A832
Database: BASE