Methodology for estimation of tissue noise power spectra in iteratively reconstructed MDCT data

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F13%3APU105140" target="_blank" >RIV/00216305:26220/13:PU105140 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Methodology for estimation of tissue noise power spectra in iteratively reconstructed MDCT data

Popis výsledku v původním jazyce

Iterative reconstruction algorithms have been recently introduced into X-ray computed tomography imaging. Enabling patient dose reduction by up to 70% without affecting image quality they deserve attention; therefore properties of noise present in iteratively reconstructed data should be examined and compared to the images reconstructed by conventionally used filtered back projection. Instead of evaluating noise in imaged phantoms or small homogeneous regions of interest in real patient data, a methodology for assessing the noise in full extent of real patient data and in diverse tissues is presented in this paper. The methodology is based on segmentation of basic tissues, subtraction of images reconstructed by different algorithms and computation of standard deviation and radial one-dimensional noise power spectra. Tissue segmentation naturally introduces errors into estimation of noise power spectra; therefore, magnitude of segmentation error is examined and is considered to be accep

Název v anglickém jazyce

Methodology for estimation of tissue noise power spectra in iteratively reconstructed MDCT data

Popis výsledku anglicky

Iterative reconstruction algorithms have been recently introduced into X-ray computed tomography imaging. Enabling patient dose reduction by up to 70% without affecting image quality they deserve attention; therefore properties of noise present in iteratively reconstructed data should be examined and compared to the images reconstructed by conventionally used filtered back projection. Instead of evaluating noise in imaged phantoms or small homogeneous regions of interest in real patient data, a methodology for assessing the noise in full extent of real patient data and in diverse tissues is presented in this paper. The methodology is based on segmentation of basic tissues, subtraction of images reconstructed by different algorithms and computation of standard deviation and radial one-dimensional noise power spectra. Tissue segmentation naturally introduces errors into estimation of noise power spectra; therefore, magnitude of segmentation error is examined and is considered to be accep

Druh

D - Stať ve sborníku

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

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Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2013

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

WSCG 2013 - Full Papers Proceedings

ISBN

978-80-86943-74-9

ISSN

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e-ISSN

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Počet stran výsledku

10

Strana od-do

243-252

Název nakladatele

Neuveden

Místo vydání

Neuveden

Místo konání akce

Plzeň

Datum konání akce

24. 6. 2013

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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