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Updated: Jun 19, 2026

A Basic Positron Emission Tomography System Constructed to Locate a Radioactive Source in a Bi-dimensional Space

A Basic Positron Emission Tomography System Constructed to Locate a Radioactive Source in a Bi-dimensional Space

Published on: February 1, 2016

Fast maximum likelihood positioning for a staggered layer scintillation PET detector.

Christoph W Lerche¹, Wenwei Bi^1,2, Mirjam Schöneck¹

¹Institute for Neuroscience and Medicine (INM-4), Forschungszentrum Jülich GmbH, Jülich, Germany.

Physics in Medicine and Biology

|August 6, 2025

Summary

This summary is machine-generated.

This study presents a fast maximum likelihood positioning (MLP) algorithm for positron emission tomography (PET) detectors, achieving high processing speeds and accurate energy resolution for improved imaging.

Keywords:

energy correction maximum likelihood position determination scintillation detector

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Published on: January 30, 2020

Area of Science:

Medical Imaging Physics
Nuclear Instrumentation
Positron Emission Tomography (PET)

Background:

Accurate energy estimation and pixel identification are crucial for positron emission tomography (PET) detector performance.
Traditional maximum likelihood positioning (MLP) algorithms can be computationally intensive, limiting real-time applications.
Staggered layer scintillation detectors offer depth-of-interaction information but require efficient positioning algorithms.

Purpose of the Study:

To develop and implement a computationally optimized, iteration-free maximum likelihood positioning (MLP) algorithm.
To enable fast energy estimation and active scintillator pixel identification in staggered layer PET detectors.
To validate the algorithm's performance on a BrainPET 7 T detector block.

Main Methods:

Developed an iteration-free MLP algorithm incorporating computational optimizations like single-instruction-multiple-data (SIMD) parallelization and multi-threading.
Implemented the algorithm for a staggered layer design with pixelated scintillators to determine gamma-ray depth of interaction.
Utilized calibration measurements and an automated script to obtain required scintillation photon counts for the MLP.

Main Results:

Achieved a maximum processing speed of approximately 22.5 million singles per second using four Intel Xeon Platinum 8168 CPUs and 60 threads.
Obtained an energy resolution of ΔE=12%±2% FWHM for the entire scintillation block after energy correction.
Demonstrated accurate scintillator pixel identification and effective energy correction for SiPM array variations.

Conclusions:

The optimized iteration-free MLP algorithm significantly enhances processing speed for PET detectors.
The method accurately determines energy and identifies scintillating pixels, achieving energy resolution close to individual pixel performance.
This fast positioning and energy determination technique is applicable to PET, SPECT, and gamma cameras.