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PETSTEP: Generation of synthetic PET lesions for fast evaluation of segmentation methods

Berthon, Beatrice, Häggström, Ida, Apte, Aditya, Beattie, Bradley J., Kirov, Assen S., Humm, John L., Marshall, Christopher, Spezi, Emiliano, Larsson, Anne and Schmidtlein, C. Ross 2015. PETSTEP: Generation of synthetic PET lesions for fast evaluation of segmentation methods. Physica Medica 31 (8) , pp. 969-980. 10.1016/j.ejmp.2015.07.139

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Abstract

This work describes PETSTEP (PET Simulator of Tracers via Emission Projection): a faster and more accessible alternative to Monte Carlo (MC) simulation generating realistic PET images, for studies assessing image features and segmentation techniques. Methods PETSTEP was implemented within Matlab as open source software. It allows generating three-dimensional PET images from PET/CT data or synthetic CT and PET maps, with user-drawn lesions and user-set acquisition and reconstruction parameters. PETSTEP was used to reproduce images of the NEMA body phantom acquired on a GE Discovery 690 PET/CT scanner, and simulated with MC for the GE Discovery LS scanner, and to generate realistic Head and Neck scans. Finally the sensitivity (S) and Positive Predictive Value (PPV) of three automatic segmentation methods were compared when applied to the scanner-acquired and PETSTEP-simulated NEMA images. Results PETSTEP produced 3D phantom and clinical images within 4 and 6 min respectively on a single core 2.7 GHz computer. PETSTEP images of the NEMA phantom had mean intensities within 2% of the scanner-acquired image for both background and largest insert, and 16% larger background Full Width at Half Maximum. Similar results were obtained when comparing PETSTEP images to MC simulated data. The S and PPV obtained with simulated phantom images were statistically significantly lower than for the original images, but led to the same conclusions with respect to the evaluated segmentation methods. Conclusions PETSTEP allows fast simulation of synthetic images reproducing scanner-acquired PET data and shows great promise for the evaluation of PET segmentation methods.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Engineering
Medicine
Subjects: R Medicine > R Medicine (General)
Uncontrolled Keywords: Positron emission tomography; Digital phantoms; Simulation; Image segmentation; Synthetic lesions
Additional Information: This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited
Publisher: Elsevier
ISSN: 1120-1797
Date of First Compliant Deposit: 30 March 2016
Date of Acceptance: 8 July 2015
Last Modified: 20 Jun 2019 19:45
URI: http://orca-mwe.cf.ac.uk/id/eprint/76211

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