Continuous criterion for parallel MRI reconstruction using B-spline approximation (PROBER)

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F07%3A03134568" target="_blank" >RIV/68407700:21230/07:03134568 - 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

Continuous criterion for parallel MRI reconstruction using B-spline approximation (PROBER)

Popis výsledku v původním jazyce

Parallel MRI is a way to use multiple receiver coils with distinct spatial sensitivities to increase the speed of the MRI acquisition. The acquisition is speeded up by undersampling in the phase-encoding direction and the resulting data loss and aliasingis compensated for by the use of the additional information obtained from several receiver coils. The task is to reconstruct an unaliased image from a series of aliased images. We have proposed an algorithm called PROBER that takes advantage of the smoothness of the reconstruction transformation in space. B-spline functions are used to approximate the reconstruction transformation. Their coefficients are estimated at once minimizing the total expected reconstruction error. This makes the reconstructionless sensitive to noise in the reference images and areas without signal in the image. We show that this approach outperforms the SENSE and GRAPPA reconstruction methods for certain coil configurations. In this article, we propose anothe

Název v anglickém jazyce

Continuous criterion for parallel MRI reconstruction using B-spline approximation (PROBER)

Popis výsledku anglicky

Parallel MRI is a way to use multiple receiver coils with distinct spatial sensitivities to increase the speed of the MRI acquisition. The acquisition is speeded up by undersampling in the phase-encoding direction and the resulting data loss and aliasingis compensated for by the use of the additional information obtained from several receiver coils. The task is to reconstruct an unaliased image from a series of aliased images. We have proposed an algorithm called PROBER that takes advantage of the smoothness of the reconstruction transformation in space. B-spline functions are used to approximate the reconstruction transformation. Their coefficients are estimated at once minimizing the total expected reconstruction error. This makes the reconstructionless sensitive to noise in the reference images and areas without signal in the image. We show that this approach outperforms the SENSE and GRAPPA reconstruction methods for certain coil configurations. In this article, we propose anothe

Druh

D - Stať ve sborníku

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

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Projekt

<a href="/cs/project/1ET101050403" target="_blank" >1ET101050403: Metody umělé inteligence v diagnostice z medicínských obrazů</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2007

Kód důvěrnosti údajů

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

Název statě ve sborníku

SPIE 2007, Medical Imaging 2007: Image Processing

ISBN

978-0-8194-6630-3

ISSN

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e-ISSN

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Počet stran výsledku

11

Strana od-do

43-53

Název nakladatele

SPIE

Místo vydání

Bellingham

Místo konání akce

San Diego, California

Datum konání akce

17. 2. 2007

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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