Local field of view imaging for alias-free undersampling with nonlinear spatial encoding magnetic fields
| Autor: | Gerrit Schultz, Daniel Gallichan, Maxim Zaitsev, Juergen Hennig, Hans Weber |
|---|---|
| Rok vydání: | 2013 |
| Předmět: |
business.industry
Iterative reconstruction Imaging phantom 030218 nuclear medicine & medical imaging 03 medical and health sciences 0302 clinical medicine Sampling (signal processing) Undersampling Encoding (memory) Radiology Nuclear Medicine and imaging Computer vision Artificial intelligence business Local field Algorithm Image resolution 030217 neurology & neurosurgery Data compression Mathematics |
| Zdroj: | Magnetic Resonance in Medicine. 71:1002-1014 |
| ISSN: | 0740-3194 |
| Popis: | Purpose: Nonlinear spatial encoding magnetic fields result inan inhomogeneous image resolution. Within this study, thischaracteristic property of nonlinear encoding is investigatedwith regard to its potential to accelerate MRI acquisitions.Theory: A dependency between k-space coverage and localresolvability of the image causes k-space samples to have aspatially localized contribution to the reconstruction of the spindensity. On the basis of this observation, a concept for alias-free data undersampling is developed, which is referred to asthe local field of view concept.Methods: On the basis of this concept, a fast sampling trajec-tory is developed. It is evaluated with simulations and experi-ments (both using a phantom and in vivo) for MRI with, as anexample, pure quadrupolar encoding fields. To demonstratethat the concept is only applicable to (spatially) nonlinearencoding, a comparison with linear encoding is provided.Results: Application of the local field of view concept resultsin a localized adaptation of the image resolution by undersam-pling higher frequency k-space samples without introducingaliasing.Conclusions: A new effect of nonlinear spatial encoding mag-netic fields was found, which allows more efficient data sam-pling and at the same time counterbalancing the naturalvariation in image resolution. |
| Databáze: | OpenAIRE |
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