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Abstract #2230

Generalized High-Pass-Filtered GRAPPA Reconstruction

Suhyung Park1, Jaeseok Park1

1Department of Brain and Cognitive Engineering, Korea University, Seoul, Korea, Republic of

Parallel imaging techniques have been widely used to reduce total acquisition time and subject motion in clinical application by using the spatial information inherent in a multiple receiver coils. However, with increasing acceleration factors, they lead to residual artifacts and amplified noises over the whole image due to corrupted data with noise. To overcome these problems, several regularization approaches have been proposed using the framework of Tikhonov regularization, such as prior-regularized GRAPPA, but a direct tradeoff between image blurring and noise amplification still remain substantially. From a different viewpoint, high pass GRAPPA (HP-GRAPPA) tried to address this problem controlling low frequency energy with high pass filter (HPF), but was still challenging to find optimal high pass band in k-space. In this work, we propose generalized HP-GRAPPA (GHP-GRAPPA) resolving a high pass band problem as a new regularization approach with high accuracy and quality.

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Keywords

acceleration achieve achieved acquisition addressed adjacent aliasing among amplification application applied applying approaches artifact artifacts assumes available balance band bands blurring bottom brain calibrating calibration career central challenging channel chart choosing class clinical close cognitive coil coils combination controlling decimated denotes develop direct divided employ employing emulate engineering entire favorable feasibility fidelity filter filtered filters find flow formulation framework frequency generalized generates geometry gradient head increasing inherent instability interpolation inverse kernel least like local locally matrix measured medical missing modeled motion narrow neighboring noise noises novel numerical observations ones onto optimal optimized outperforms overall overcome parallel park pass perspective prior problem problems procedure process projection properties proposed receiver reconstructed reconstruction reconstructions reduce reducing reduction regionally regularization regularized remains republic residual respectively sampling scanner schematic segmented sets several slice solution space spanned spatial spoiled squares still subject subspace substantially support suppress suppressing theory transformed trio twelve volunteer whole wide widely world zoomed