Improving the contrast-to-noise ratio by averaging in scintillation detectors
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68378297%3A_____%2F17%3A00480141" target="_blank" >RIV/68378297:_____/17:00480141 - isvavai.cz</a>
Výsledek na webu
<a href="http://ieeexplore.ieee.org/document/8069616/" target="_blank" >http://ieeexplore.ieee.org/document/8069616/</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/NSSMIC.2016.8069616" target="_blank" >10.1109/NSSMIC.2016.8069616</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Improving the contrast-to-noise ratio by averaging in scintillation detectors
Popis výsledku v původním jazyce
From the point of view of the image quality, the contrast-to-noise ratio (CNR) is a crucial parameter. In case of the scintillation detectors, which are widely used in X-ray radiography and computed tomography, CNR is determined by the static image noise caused mainly by the non-uniformity of the response of particular pixels, and by the stochastic noise, composed of the inherent noise of the detector and the X-ray beam fluctuation. The static noise can be suppressed using appropriate correction methods, such as the flat field correction. The stochastic component of noise can be lowered by averaging of more images of the same scene, but this approach leads to an increased time of the tomography, which can be an undesirable effect. This paper shows a method that separates the stochastic noise component from the static noise component and thus allows to determine the maximum reachable CNR in the given case and the minimum number of images to be averaged for reaching required CNR. The method is intended to be used for optimized setting of the detector and X-ray source parameters in tomography to obtain the best possible results in a reasonable time.
Název v anglickém jazyce
Improving the contrast-to-noise ratio by averaging in scintillation detectors
Popis výsledku anglicky
From the point of view of the image quality, the contrast-to-noise ratio (CNR) is a crucial parameter. In case of the scintillation detectors, which are widely used in X-ray radiography and computed tomography, CNR is determined by the static image noise caused mainly by the non-uniformity of the response of particular pixels, and by the stochastic noise, composed of the inherent noise of the detector and the X-ray beam fluctuation. The static noise can be suppressed using appropriate correction methods, such as the flat field correction. The stochastic component of noise can be lowered by averaging of more images of the same scene, but this approach leads to an increased time of the tomography, which can be an undesirable effect. This paper shows a method that separates the stochastic noise component from the static noise component and thus allows to determine the maximum reachable CNR in the given case and the minimum number of images to be averaged for reaching required CNR. The method is intended to be used for optimized setting of the detector and X-ray source parameters in tomography to obtain the best possible results in a reasonable time.
Klasifikace
Druh
D - Stať ve sborníku
CEP obor
—
OECD FORD obor
21100 - Other engineering and technologies
Návaznosti výsledku
Projekt
<a href="/cs/project/LO1219" target="_blank" >LO1219: Udržitelný pokročilý rozvoj CET</a><br>
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Ostatní
Rok uplatnění
2017
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název statě ve sborníku
Nuclear Science Symposium, Medical Imaging Conference and Room-Temperature Semiconductor Detector Workshop (NSS/MIC/RTSD), 2016 IEEE
ISBN
978-1-5090-1642-6
ISSN
—
e-ISSN
—
Počet stran výsledku
3
Strana od-do
—
Název nakladatele
IEEE
Místo vydání
S.l.
Místo konání akce
Strasbourg
Datum konání akce
29. 10. 2016
Typ akce podle státní příslušnosti
WRD - Celosvětová akce
Kód UT WoS článku
—