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http://dx.doi.org/10.7742/jksr.2022.16.6.697

Deep Learning Applied Method for Acquisition of Digital Position Signal of PET Detector  

Byungdu, Jo (Department of Radiological Science, Dongseo University)
Seung-Jae, Lee (Department of Radiological Science, Dongseo University)
Publication Information
Journal of the Korean Society of Radiology / v.16, no.6, 2022 , pp. 697-702 More about this Journal
Abstract
For imaging in positron emission tomography(PET), it is necessary to measure the position of the scintillation pixel interacting with the gamma rays incident on the detector. To this end, in the conventional system, a flood image of the scintillation pixel is obtained, the imaged area of each scintillation pixel is separated, and the position of the scintillation pixel is specified and acquired as a digital signal. In this study, a deep learning method was applied based on the signal formed by the photosensor of the detector, and a method was developed to directly acquire a digital signal without going through various procedures. DETECT2000 simulation was performed to verify this and evaluate the accuracy of position measurement. A detector was constructed using a 6 × 6 scintillation pixel array and a 4 × 4 photosensor, and a gamma ray event was generated at the center of the scintillation pixel and summed into four channels of signals through the Anger equation. After training the deep learning model using the acquired signal, the positions of gamma-ray events that occurred in different depth directions of the scintillation pixel were measured. The results showed accurate results at every scintillation pixel and position. When the method developed in this study is applied to the PET detector, it will be possible to measure the position of the scintillation pixel with a digital signal more conveniently.
Keywords
Positron emission Tomography; Position determination; Deep learning; Simulation;
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