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Abstract #3352

Optimally Weighted Average (OWA) of Phase-Sensitive Data

Yiyun Dong1, Qing-San Xiang2, and Michael N Hoff3
1Physics, University of Washington, Seattle, WA, United States, 2Radiology, University of British Columbia, Vancouver, BC, Canada, 3Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States

Synopsis

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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Keywords