Reconstruction and visualization of irregularly sampled three- and four-dimensional ultrasound data for cerebrovascular applications

Although recent studies have demonstrated the potential value of compounded data for improvement in signal-to-noise ratio and speckle contrast for three-dimensional (3-D) ultrasonography, clinical applications are lacking. We investigated the potential of six degrees-of-freedom (6-DOF) scanhead posi...

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Hauptverfasser: Meairs, Stephen (VerfasserIn) , Beyer, Jens (VerfasserIn) , Hennerici, Michael G. (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: 15 March 2000
In: Ultrasound in medicine & biology
Year: 2000, Jahrgang: 26, Heft: 2, Pages: 263-272
ISSN:1879-291X
DOI:10.1016/s0301-5629(99)00130-1
Online-Zugang:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1016/s0301-5629(99)00130-1
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Verfasserangaben:Stephen Meairs, Jens Beyer and Michael Hennerici
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Zusammenfassung:Although recent studies have demonstrated the potential value of compounded data for improvement in signal-to-noise ratio and speckle contrast for three-dimensional (3-D) ultrasonography, clinical applications are lacking. We investigated the potential of six degrees-of-freedom (6-DOF) scanhead position and orientation measurement (POM) devices for registration of in vivo multiplanar, irregularly sampled ultrasound (US) images to a regular 3-D volume space. The results demonstrate that accurate spatial and temporal registration of four-dimensional (4-D) US data can be achieved using a 6-DOF scanhead tracking system. For reconstruction of arbitrary, irregularly sampled US data, we introduce a technique based upon a weighted, ellipsoid Gaussian convolution kernel. Volume renderings of 3-D and 4-D compounded in vivo US data are presented. The results, although restricted to the field of cerebrovascular disease, will be of value to other applications of 3-D sonography, particularly those in which compounding of data through irregular sampling may provide superior information on tissue or vessel structure.
Beschreibung:Gesehen am 13.06.2022
Beschreibung:Online Resource
ISSN:1879-291X
DOI:10.1016/s0301-5629(99)00130-1