Non-Cartesian parallel imaging reconstruction.
Non-Cartesian parallel imaging has played an important role in reducing data acquisition time in MRI. The use of non-Cartesian trajectories can enable more efficient coverage of k-space, which can be leveraged to reduce scan times. These trajectories can be undersampled to achieve even faster scan t...
| Publicado en: | Journal of Magnetic Resonance Imaging Vol. 40; no. 5; pp. 1022 - 1041 |
|---|---|
| Autores principales: | , , , , |
| Formato: | review Journal Article |
| Publicado: |
Wiley-Blackwell
Nov2014
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=109681537&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 109681537 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10531807 O63 jtl: Journal of Magnetic Resonance Imaging issn: 10531807 maglogo: Y pubinfo: dt: Nov2014 vid: 40 iid: 5 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 109681537 NLM24408499 2012768653 10.1002/jmri.24521 NLM24408499 PMC4092190 109681537 ppf: 1022 ppct: 19 formats: tig: atl: Non-Cartesian parallel imaging reconstruction. aug: au: Wright, Katherine L Hamilton, Jesse I Griswold, Mark A Gulani, Vikas Seiberlich, Nicole sug: ab: Non-Cartesian parallel imaging has played an important role in reducing data acquisition time in MRI. The use of non-Cartesian trajectories can enable more efficient coverage of k-space, which can be leveraged to reduce scan times. These trajectories can be undersampled to achieve even faster scan times, but the resulting images may contain aliasing artifacts. Just as Cartesian parallel imaging can be used to reconstruct images from undersampled Cartesian data, non-Cartesian parallel imaging methods can mitigate aliasing artifacts by using additional spatial encoding information in the form of the nonhomogeneous sensitivities of multi-coil phased arrays. This review will begin with an overview of non-Cartesian k-space trajectories and their sampling properties, followed by an in-depth discussion of several selected non-Cartesian parallel imaging algorithms. Three representative non-Cartesian parallel imaging methods will be described, including Conjugate Gradient SENSE (CG SENSE), non-Cartesian generalized autocalibrating partially parallel acquisition (GRAPPA), and Iterative Self-Consistent Parallel Imaging Reconstruction (SPIRiT). After a discussion of these three techniques, several potential promising clinical applications of non-Cartesian parallel imaging will be covered. pubtype: Academic Journal doctype: review Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|