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

Result code in 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>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

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

Original language description

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

Czech name

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

Czech description

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

Type

D - Article in proceedings

CEP classification

JD - Use of computers, robotics and its application

OECD FORD branch

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Project

<a href="/en/project/1ET101050403" target="_blank" >1ET101050403: Artificial inteligence methods in diagnostics from medical images</a><br>

Continuities

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

Publication year

2007

Confidentiality

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

Article name in the collection

SPIE 2007, Medical Imaging 2007: Image Processing

ISBN

978-0-8194-6630-3

ISSN

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e-ISSN

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Number of pages

11

Pages from-to

43-53

Publisher name

SPIE

Place of publication

Bellingham

Event location

San Diego, California

Event date

Feb 17, 2007

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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