In recent years, the clinical status of positron emission tomography(PET)/computed tomography(CT) in achieving
more accurate staging of lung cancer has been established and the technology has been enthusiastically
accepted by the medical community. However, its capability in chest imaging is still limited by several physical
factors. As a result of typical PET/CT imaging protocol, respiration-averaged PET data and free of respiration-averaged
CT data are collected in a PET/CT scanning. In this work, we investigate the effects of respiration
motion. We employ mathematical and Monte-Carlo simulations for generating PET/CT data. We scale a
Zubal phantom to generate 30 phantoms having various sizes in order to represent different torso anatomic
states during respiration. Images reconstructed from selected scaling PET data using the respective scaling
PET attenuation maps serve as baseline results. PET/CT imaging protocol is simulated by reconstruction
from respiration-averaged PET data with the selected PET attenuation maps. We also reconstruct PET images
from respiratory-averaged PET data with respiration-averaged PET attenuation maps, which simulates conventional
PET imaging protocol. We will compare the resulting images reconstructed from the above-mentioned
approaches to evaluate the effects of respiration motion in PET/CT.
We present our work toward implementing all-digital signal processing for Positron Emission Tomography (PET)
event detection. In the conventional PET system, proper calibration and extending event processing are challenging
tasks due to the huge number of channels and multiplexing of input signals in the mixed-signal front-end.
To alleviate such limitations, we have proposed a simple all-digital PET system utilizing digital signal processing
(DSP) technologies for analyzing event pulses generated in PET. In this work, we implement a Gaussian shaper
circuit for scintillation pulses, which followed by a moderate sampling rate Analog-to-Digital Converter (ADC).
We also evaluate two DSP algorithms for extracting time information from the digitized pulse samples, and the
two algorithms examined could generate a coincidence timing resolution of ~ 2.4ns FWHM, by using a 125MSps
sampling rate ADC.
KEYWORDS: Positron emission tomography, Data acquisition, Clocks, Calibration, Signal processing, Digital signal processing, Crystals, Field programmable gate arrays, Sensors, Signal detection
Positron emission tomography~(PET) systems employ mixed-signal front-end to carry out relatively simple, and ad hoc, processing of the charge pulses generated upon event detection. To obtain, and maintain over time, proper calibrations of the mixed-signal circuitry for generating accurate event information is a challenging task due to the simplicity of the event processing, and the huge number of channels and multiplexing of the input signals found in modern PET systems. It is also difficult to modify or extend the event-processing technologies when needs arise because it would involve making changes to the circuitry. These limitations can be circumvented by applying digital signal-processing technologies for analyzing event pulses generated in PET. With digital technologies, optimized event-processing algorithms can be implemented and they can be modified or extended with ease when needed. The resulting PET data-acquisition (DAQ) system is easier to calibrate and maintain, can generate more accurate event information, and has better extendibility. In this paper, we present our work toward developing a scalable all-digital DAQ system for PET, built upon a personal-computer platform for reducing cost. We will present the overall architecture of this digital DAQ system, and describe our implementations of several components of the system.
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