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Abstract #5165

Improved SPIRiT Operator for Joint Reconstruction of Multiple T2-weighted Images

Toygan Kilic1,2, Efe Ilicak1,2, Tolga Çukur1,2, and Emine Ulku Saritas1,2

1Electrical and Electronics Engineering, Bilkent University, Ankara, Turkey, 2National Magnetic Resonance Research Center, Bilkent University, Ankara, Turkey

Recently, compressed-sensing (CS) was proposed to jointly reconstruct undersampled multi-contrast datasets to exploit the common structural features therein. Here, we propose a method to improve joint reconstruction of multi-contrast acquisitions. Inspired by the SPIRiT framework for parallel imaging, our method linearly synthesizes missing data for each contrast from neighboring k-space data for all contrasts. To improve reconstruction quality, the proposed method high-pass filters calibration data to emphasize the weight of intermediate spatial frequencies in the interpolation operator. Phantom and in vivo results at 3T indicate that the proposed method outperforms reconstructions with conventionally estimated interpolators.

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