Model-based Extraction of Input and Organ Functions in Dynamic Medical Imaging

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F13%3A00208567" target="_blank" >RIV/68407700:21340/13:00208567 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/67985556:_____/13:00397761 RIV/00216208:11110/14:10287250 RIV/00064165:_____/14:10287250

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Model-based Extraction of Input and Organ Functions in Dynamic Medical Imaging

Popis výsledku v původním jazyce

Availability of input and organ functions is a prerequisite for analysis of dynamic image sequences in scintigraphy and positron emission tomography (PET) via kinetic models. This task is typically done manually by a human operator who may be unreliable.We propose a probabilistic model based on physiological assumption that time-activity curves (TACs) arise as a convolution of an input function and organ-specific kernels. The model is solved via the Variational Bayes estimation procedure and provides estimates of the organ images, the TACs, and the input function as results. The ability of the resulting algorithm to extract the input function is tested on data from dynamic renal scintigraphy. The estimated input function was compared with the common estimate based on manual selection of the heart ROI. The method was applied to the problem of relative renal function estimation and the results are compared with competing techniques. Results of comparison on a dataset of 99 patients demo

Název v anglickém jazyce

Model-based Extraction of Input and Organ Functions in Dynamic Medical Imaging

Popis výsledku anglicky

Availability of input and organ functions is a prerequisite for analysis of dynamic image sequences in scintigraphy and positron emission tomography (PET) via kinetic models. This task is typically done manually by a human operator who may be unreliable.We propose a probabilistic model based on physiological assumption that time-activity curves (TACs) arise as a convolution of an input function and organ-specific kernels. The model is solved via the Variational Bayes estimation procedure and provides estimates of the organ images, the TACs, and the input function as results. The ability of the resulting algorithm to extract the input function is tested on data from dynamic renal scintigraphy. The estimated input function was compared with the common estimate based on manual selection of the heart ROI. The method was applied to the problem of relative renal function estimation and the results are compared with competing techniques. Results of comparison on a dataset of 99 patients demo

Druh

D - Stať ve sborníku

CEP obor

BB - Aplikovaná statistika, operační výzkum

OECD FORD obor

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Projekt

<a href="/cs/project/GA13-29225S" target="_blank" >GA13-29225S: Slepá dekonvoluce obrazu v limitních podmínkách</a><br>

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

Computational Vision and Medical Image Processing (VipIMAGE 2013)

ISBN

978-1-138-00081-0

ISSN

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e-ISSN

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Počet stran výsledku

6

Strana od-do

75-80

Název nakladatele

CRC Press/Balkema

Místo vydání

Leiden

Místo konání akce

Funchal

Datum konání akce

14. 10. 2013

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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