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An algorithm for automatic crystal identification in pixelated scintillation detectors using thin plate splines and Gaussian mixture models

Positron emission tomography (PET) is a non-invasive imaging technique which utilizes positron-emitting radiopharmaceuticals (PERs) to characterize biological processes in tissues of interest. A PET scanner is usually composed of multiple scintillation crystal detectors placed in a ring so as to capture coincident photons from a position annihilation. These detectors require a crystal lookup table (CLUT) to map the detector response to the crystal of interaction. These CLUTs must be accurate, lest events get mapped to the wrong crystal of interaction degrading the final image quality. This work describes an automated algorithm, for CLUT generation, focused around Gaussian Mixture Models (GMM) with Thin Plate Splines (TPS). The algorithm was tested with flood image data collected from 16 detectors. The method maintained at least 99.8% accuracy across all tests. This method is considerably faster than manual techniques and can be adapted to different detector configurations. / February 2016

Identiferoai:union.ndltd.org:MANITOBA/oai:mspace.lib.umanitoba.ca:1993/31103
Date19 January 2016
CreatorsSchellenberg, Graham
ContributorsGoertzen, Andrew (Physics and Astronomy), Pistorius, Stephen (Physics and Astronomy) LoVetri, Joe (Electrical and Computer Engineering)
Source SetsUniversity of Manitoba Canada
Detected LanguageEnglish

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