English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
Add to Basket
  Local TagsRelease HistoryDetailsSummary

Released
Poster

Smart Averaging: SNR Improvement by Retrospective Filtering

MPS-Authors
/persons/resource/persons84145

Pohmann,  R
Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

/persons/resource/persons84187

Scheffler,  K
Max Planck Institute for Biological Cybernetics, Max Planck Society;
Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society;

External Resource

Link
(Any fulltext)

Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)
There are no public fulltexts stored in PuRe
Supplementary Material (public)
There is no public supplementary material available
Citation

Pohmann, R., & Scheffler, K. (2016). Smart Averaging: SNR Improvement by Retrospective Filtering. Poster presented at 24th Annual Meeting and Exhibition of the International Society for Magnetic Resonance in Medicine (ISMRM 2016), Singapore.


Cite as: https://hdl.handle.net/21.11116/0000-0000-7BAB-6
Abstract
Averaging is a frequently used way to increase the SNR of a measurement. Here we show that spending the additional time for increasing the spatial resolution and applying a retrospective k-space filter can yield a higher SNR gain than conventional averaging. For weighting in two phase encoding directions, this can increase the SNR by up to 25. For 3D weighting, SNR gain can reach 57, if the additional acquired k-space points are used to increase the readout duration, and 38 for equal duration for weighted and unweighted acquisition.