Reconstruction of phase images for GRAPPA accelerated Magnetic Resonance Imaging

Quantitative imaging of intrinsic magnetic tissue properties using MRI signal phase: An approach to in vivo brain iron metabolism?

“…Magnitude and phase images were obtained after combining the complex multi-channel data using uniform sensitivity reconstruction (Ros et al, 2009). Subsequently, phase aliasing was resolved with a 3D phase unwrapping algorithm (Abdul-Rahman et al, 2007) and the initial phase distribution, φ 0 (r → ), was determined from the phase images of both ToF-SWI echoes according to Eq.…”

Quantitative susceptibility mapping for investigating subtle susceptibility variations in the human brain

“…Multi-channel GRE magnitude and phase images of the volunteer experiments were combined using uniform sensitivity reconstruction on the MR scanner reconstruction system (Ros et al, 2009). Any further in vivo data processing was carried out in MATLAB (version 2010b, The MathWorks, Natick, MA) on a dual-processor workstation (Quad-Core Xeon E5520, Intel, Santa Clara, CA) with 24 GB RAM.…”

Combining phase images from multi‐channel RF coils using 3D phase offset maps derived from a dual‐echo scan

“…Other approaches, such as self‐calibrated SENSE (12) and adaptive filtering (13), use sophisticated methods to estimate coil sensitivities without a reference image. Although these lead to improved magnitude images, phase images generated with these reference‐free methods do not necessarily represent the true phase (as measured with a volume coil) (14, 15). Self‐calibrated SENSE has recently been extended for the optimized reconstruction of phase and complex images (14).…”

“…These can be identified using a variety of algorithms (16, 17) and removed to restore the full phase range. The second problem is that individual receivers are subject to different, spatially varying, phase offsets which mean that combining phase information naively, e.g., from summed complex data or by weighting each phase image by the respective magnitude image, leads to interference and regions of signal cancellation (15). Phase images calculated in this way have generally low SNR and frequently show wraps that terminate within the object (corresponding to complete signal cancellation), known as “open‐ended fringe lines.” One approach to combining phase images from multiple receivers is to unwrap phase images then apply a high‐pass filter (which removes phase offsets, as low frequency features) before calculating a weighted mean over channels (e.g.…”