Keywords: Image Reconstruction, Image Reconstruction, Phase-preserved image combination, Optimally weighted average, Coil-combination
Motivation: To produce accurate phase-sensitive MRI image reconstructions with effective phase-preserving methods, overcoming limitations of current data combination techniques.
Goal(s): To investigate the optimally weighted average (OWA) in combining multi-component phase-based images and achieve artifact- and noise-reduced MRI reconstructions.
Approach: The Lagrange multiplier is used to develop the theoretical foundation of extending OWA to a multi-component image combination scenario. Performance is validated by combining RF-channel-specific bSSFP off-resonant phase accumulation data in a phantom.
Results: The OWA used regional variance weighting with an appropriate kernel size to minimize component-specific artifacts and general noise, outperforming the complex sum method.
Impact: OWA data combination significantly enhances phase-preserving MRI reconstructions by minimizing artifacts and noise, outperforming the complex sum method. This technique promises improved diagnostic accuracy and image quality, beneficial for clinical applications where phase-sensitive data reconstruction is crucial.
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