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Three-dimensional Fourier encoding of simultaneously excited slices: generalized acquisition and reconstruction
Benjamin Zahneisen1, Benedikt A Poser, Thomas Ernst
1Department of Medicine, University of Hawaii, John A. Burns School of Medicine, Honolulu, Hawaii, USA.
This study introduces a generalized 3D framework for simultaneous multislice (SMS) imaging, enhancing speed in MRI. The new method simplifies reconstruction for both Cartesian and non-Cartesian SMS acquisitions.
Area of Science:
- Magnetic Resonance Imaging (MRI)
- Medical Imaging Physics
Background:
- Simultaneous multislice (SMS) acquisitions accelerate imaging by combining single-shot sampling with slice-dimension acceleration.
- Current 2D descriptions of SMS sampling and reconstruction are established but limited.
- Three-dimensional (3D) volumetric acquisitions were previously required for slice acceleration.
Purpose of the Study:
- To present a generalized 3D Fourier encoding and reconstruction formalism for SMS acquisitions.
- To extend SMS methods to non-Cartesian sampling and reconstruction.
- To provide a unified framework applicable to various SMS acquisition types.
Main Methods:
- Defined an "SMS 3D" k-space where the field of view in the slice direction accommodates multiple slices.
- Viewed SMS acceleration as undersampling within this 3D k-space, allowing flexible distribution between in-plane and slice directions.
- Demonstrated reconstruction using SMS sensitivity encoding and non-Cartesian SMS imaging with blipped spiral trajectories.
Main Results:
- Successfully applied the SMS 3D k-space formalism to phantom and in vivo brain imaging.
- Included data acquired with blipped-controlled aliasing in parallel imaging (CAIPI) sampling.
- Demonstrated SMS sensitivity encoding reconstruction and non-Cartesian SMS imaging.
Conclusions:
- The 3D k-space approach enables the full framework of reconstruction methods for SMS acquisitions.
- Blipped-CAIPI is a specific instance of undersampling the SMS 3D k-space.
- Extending SMS methods to non-Cartesian 3D sampling and reconstruction is straightforward.
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