Front-end data processing of new positron emission tomography demonstrator
Moradi, Soudabeh (2014)
Moradi, Soudabeh
2014
Tietotekniikan koulutusohjelma
Tieto- ja sähkötekniikan tiedekunta - Faculty of Computing and Electrical Engineering
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Hyväksymispäivämäärä
2014-03-05
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tty-201402211090
https://urn.fi/URN:NBN:fi:tty-201402211090
Tiivistelmä
Axial PET (AX-PET) is a novel geometrical concept for positron emission tomography (PET) based on stacks of long scintillating crystals aligned axially with the bore axis and layers of wavelength shifter (WLS) strips placed orthogonal to them. The novel structure allows for detection of depth of interaction using the stack of crystals with WLS strips thus avoiding the parallax error presented due to different depths of interaction in the crystals. Therefore, existing compromise between the sensitivity and spatial resolution in the conventional PET scanners is overcome and highly sensitive scanners with improved spatial resolution can be produced.
This thesis presents a new AX-PET demonstrator, which was built in Tampere University of Technology. The aim of the thesis is to define 3-dimensional coordinate system for this demonstrator as well as to determine the location of coincidence events in this system. The demonstrator consists of four modules each of which are containing two LYSO crystal layers and two layers of WLS strips aligned orthogonal to the crystals. The crystals and WLS strips are read individually. The signals coming from the crystals determine the X- and Y-coordinates of the hit and the signals from the WLS strips define its Z-coordinate. We created a small test data with MATLAB for examination of our methods. Subsequently, the coincidence events were determined using a coincidence window of 3 ns. For defining the location of the coincidence events, we first calculated its location inside the module (intramodular hit location) using the hit crystal and the corresponding WLS strip(s). Then we converted the location data to the scanner coordinate system (intermodular hit location). In order to speed up the positioning of the coincidence events, we created lookup tables such that 3D position of all possible interaction points were calculated beforehand and recorded in these tables. This way, it was not necessary to repeat all the calculations for positioning of each detected event, but the position was just selected from the lookup tables. This approach worked efficiently for positioning the coincidence events of our test data. The efficiency can be approved using a real test data, where large amount of coincidence events are detected.
This thesis presents a new AX-PET demonstrator, which was built in Tampere University of Technology. The aim of the thesis is to define 3-dimensional coordinate system for this demonstrator as well as to determine the location of coincidence events in this system. The demonstrator consists of four modules each of which are containing two LYSO crystal layers and two layers of WLS strips aligned orthogonal to the crystals. The crystals and WLS strips are read individually. The signals coming from the crystals determine the X- and Y-coordinates of the hit and the signals from the WLS strips define its Z-coordinate. We created a small test data with MATLAB for examination of our methods. Subsequently, the coincidence events were determined using a coincidence window of 3 ns. For defining the location of the coincidence events, we first calculated its location inside the module (intramodular hit location) using the hit crystal and the corresponding WLS strip(s). Then we converted the location data to the scanner coordinate system (intermodular hit location). In order to speed up the positioning of the coincidence events, we created lookup tables such that 3D position of all possible interaction points were calculated beforehand and recorded in these tables. This way, it was not necessary to repeat all the calculations for positioning of each detected event, but the position was just selected from the lookup tables. This approach worked efficiently for positioning the coincidence events of our test data. The efficiency can be approved using a real test data, where large amount of coincidence events are detected.