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Multiple particle tracking in PEPT using Voronoi tessellations

An algorithm is presented which makes use of three-dimensional Voronoi tessellations to track up to 20 tracers using a PET scanner. The lines of response generated by the PET scanner are discretized into sets of equidistant points, and these are used as the input seeds to the Voronoi tessellation. F...

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Main Author: Blakemore, Dylan
Other Authors: Govender, Indresan
Format: Thesis
Language:English
Published: Department of Mechanical Engineering 2017
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access_status_str Open Access
author Blakemore, Dylan
author2 Govender, Indresan
author_browse Blakemore, Dylan
Govender, Indresan
author_facet Govender, Indresan
Blakemore, Dylan
author_sort Blakemore, Dylan
collection Thesis
description An algorithm is presented which makes use of three-dimensional Voronoi tessellations to track up to 20 tracers using a PET scanner. The lines of response generated by the PET scanner are discretized into sets of equidistant points, and these are used as the input seeds to the Voronoi tessellation. For each line of response, the point with the smallest Voronoi region is located; this point is assumed to be the origin of the corresponding line of response. Once these origin points have been determined, any outliers are removed, and the remaining points are clustered using the DBSCAN algorithm. The centroid of each cluster is classified as a tracer location. Once the tracer locations are determined for each time frame in the experimental data set, a custom multiple target tracking algorithm is used to associate identical tracers from frame to frame. Since there are no physical properties to distinguish the tracers from one another, the tracking algorithm uses velocity and position to extrapolate the locations of existing tracers and match the next frame's tracers to the trajectories. A series of experiments were conducted in order to test the robustness, accuracy and computational performance of the algorithm. A measure of robustness is the chance of track loss, which occurs when the algorithm fails to match a tracer location with its trajectory, and the track is terminated. The chance of track loss increases with the number of tracers; the acceleration of the tracers; the time interval between successive frames; and the proximity of tracers to each other. In the case of two tracers colliding, the two tracks merge for a short period of time, before separating and become distinguishable again. Track loss also occurs when a tracer leaves the field of view of the scanner; on return it is treated as a new object. The accuracy of location of the algorithm was found to be slightly affected by tracer velocity, but is much more dependent on the distance between consecutive points on a line of response, and the number of lines of response used per time frame. A single tracer was located to within 1.26mm. This was compared to the widely accepted Birmingham algorithm, which located the same tracer to within 0.92mm. Precisions of between 1.5 and 2.0mm were easily achieved for multiple tracers. The memory usage and processing time of the algorithm are dependent on the number of tracers used in the experiment. It was found that the processing time per frame for 20 tracers was about 15s, and the memory usage was 400MB. Because of the high processing times, the algorithm as is is not feasible for practical use. However, the location phase of the algorithm is massively parallel, so the code can be adapted to significantly increase the efficiency.
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institution University of Cape Town (South Africa)
language eng
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license_str Not specified — see source repository
provenance_str_mv Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository
publishDate 2017
publishDateRange 2017
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publisher Department of Mechanical Engineering
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spelling oai:open.uct.ac.za:11427/22929 Multiple particle tracking in PEPT using Voronoi tessellations Blakemore, Dylan Govender, Indresan McBride, Andrew Trevor Mechanical Engineering An algorithm is presented which makes use of three-dimensional Voronoi tessellations to track up to 20 tracers using a PET scanner. The lines of response generated by the PET scanner are discretized into sets of equidistant points, and these are used as the input seeds to the Voronoi tessellation. For each line of response, the point with the smallest Voronoi region is located; this point is assumed to be the origin of the corresponding line of response. Once these origin points have been determined, any outliers are removed, and the remaining points are clustered using the DBSCAN algorithm. The centroid of each cluster is classified as a tracer location. Once the tracer locations are determined for each time frame in the experimental data set, a custom multiple target tracking algorithm is used to associate identical tracers from frame to frame. Since there are no physical properties to distinguish the tracers from one another, the tracking algorithm uses velocity and position to extrapolate the locations of existing tracers and match the next frame's tracers to the trajectories. A series of experiments were conducted in order to test the robustness, accuracy and computational performance of the algorithm. A measure of robustness is the chance of track loss, which occurs when the algorithm fails to match a tracer location with its trajectory, and the track is terminated. The chance of track loss increases with the number of tracers; the acceleration of the tracers; the time interval between successive frames; and the proximity of tracers to each other. In the case of two tracers colliding, the two tracks merge for a short period of time, before separating and become distinguishable again. Track loss also occurs when a tracer leaves the field of view of the scanner; on return it is treated as a new object. The accuracy of location of the algorithm was found to be slightly affected by tracer velocity, but is much more dependent on the distance between consecutive points on a line of response, and the number of lines of response used per time frame. A single tracer was located to within 1.26mm. This was compared to the widely accepted Birmingham algorithm, which located the same tracer to within 0.92mm. Precisions of between 1.5 and 2.0mm were easily achieved for multiple tracers. The memory usage and processing time of the algorithm are dependent on the number of tracers used in the experiment. It was found that the processing time per frame for 20 tracers was about 15s, and the memory usage was 400MB. Because of the high processing times, the algorithm as is is not feasible for practical use. However, the location phase of the algorithm is massively parallel, so the code can be adapted to significantly increase the efficiency. 2017-01-23T09:25:03Z 2017-01-23T09:25:03Z 2016 Master Thesis Masters MSc http://hdl.handle.net/11427/22929 eng application/pdf Department of Mechanical Engineering Faculty of Engineering and the Built Environment University of Cape Town
spellingShingle Mechanical Engineering
Blakemore, Dylan
Multiple particle tracking in PEPT using Voronoi tessellations
thesis_degree_str Master's
title Multiple particle tracking in PEPT using Voronoi tessellations
title_full Multiple particle tracking in PEPT using Voronoi tessellations
title_fullStr Multiple particle tracking in PEPT using Voronoi tessellations
title_full_unstemmed Multiple particle tracking in PEPT using Voronoi tessellations
title_short Multiple particle tracking in PEPT using Voronoi tessellations
title_sort multiple particle tracking in pept using voronoi tessellations
topic Mechanical Engineering
url http://hdl.handle.net/11427/22929
work_keys_str_mv AT blakemoredylan multipleparticletrackinginpeptusingvoronoitessellations