Three dimensional k-space trajectory design using genetic algorithms

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dc.contributor.authorSabat, S
dc.contributor.authorMir, R
dc.contributor.authorGuarini, M
dc.contributor.authorGuesalaga, A
dc.contributor.authorIrarrazaval, P
dc.date.accessioned2024-01-10T12:44:22Z
dc.date.available2024-01-10T12:44:22Z
dc.date.issued2003
dc.description.abstractImage quality and total scan time in MRI are determined in large part by the trajectory employed to sample the Fourier space. Each trajectory has different properties like coverage of k-space, scan time, sensitivity to off-resonance conditions, etc. These properties are often contradictory, therefore a universal optimal trajectory does not exist and ultimately, it will depend on the image characteristics sought. Most trajectories used today are designed based on intuition and k-space analysis more than with optimization methods. This work presents a 3D k-space trajectory design method based on Genetic Algorithm optimization. Genetic Algorithms have been chosen because they are particularly good for searching large solution spaces. They emulate the natural evolutionary process allowing better offsprings to survive. The objective function searches the maximum of the trajectory's k-space coverage subject to hardware constraints for a fixed scanning time using the trajectory's torsion as its optimization variable.
dc.description.abstractThe method proved to be effective for generating k-space trajectories. They are compared with well-established trajectories. The results of simulated experiments show that they can be appropriate for image acquisition under certain special conditions, like off-resonance and undersampling. This design method can be extended to include other objective functions for different behaviors. (C) 2003 Elsevier Inc. All rights reserved.
dc.fechaingreso.objetodigital2024-04-11
dc.format.extent10 páginas
dc.fuente.origenWOS
dc.identifier.doi10.1016/S0730-725X(03)00174-7
dc.identifier.issn0730-725X
dc.identifier.pubmedidMEDLINE:14559340
dc.identifier.urihttps://doi.org/10.1016/S0730-725X(03)00174-7
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/77668
dc.identifier.wosidWOS:000185987800009
dc.information.autorucIngeniería;Guarini M;S/I;99643
dc.information.autorucIngeniería;Guesalaga A;S/I;63871
dc.information.autorucIngeniería;Irarrázaval P;S/I;57376
dc.issue.numero7
dc.language.isoen
dc.nota.accesocontenido parcial
dc.pagina.final764
dc.pagina.inicio755
dc.publisherELSEVIER SCIENCE INC
dc.revistaMAGNETIC RESONANCE IMAGING
dc.rightsacceso restringido
dc.subjectk-space
dc.subjectgenetic algorithm
dc.subjecttrajectory design
dc.subjectIMAGING METHODS
dc.subject.ods03 Good Health and Well-being
dc.subject.odspa03 Salud y bienestar
dc.titleThree dimensional k-space trajectory design using genetic algorithms
dc.typeartículo
dc.volumen21
sipa.codpersvinculados99643
sipa.codpersvinculados63871
sipa.codpersvinculados57376
sipa.indexWOS
sipa.indexScopus
sipa.trazabilidadCarga SIPA;09-01-2024
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