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Abstract #3738

Whitening of colored noise in PROPELLER using iterative regularized PICO reconstruction

Jyh-Miin Lin 1 , Andrew Patterson 2 , Hing-Chiu Chang 3 , Tzu-Chao Chuang 4 , Hsiao-Wen Chung 5 , Jonathan H. Gillard 1 , and Martin J. Graves 2

1 Department of Radiolgoy, University of Cambridge, Cambridge, Cambridgeshire, United Kingdom, 2 Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom, 3 Brain Imaging and Analysis Center, Duke University Medical Center, NC, United States, 4 Department of Electrical Engineering, National Sun Yat-sen University, Kaohsiung, Taiwan, Taiwan, 5 Department of Electrical Engineering, National Taiwan University, Taiwan, Taiwan

The colored noise pattern in periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) images is described theoretically by Cramér-Rao lower bound (CRLB), followed by confirmation using simulation and phantom studies. An iterative regularized method named Pseudo-Inverse as COnstraint (PICO) for reconstructing PROPELLER images is proposed and tested on phantom images to examine the whitening of noise power spectra at various angular under-sampling factors. Comparison against conventionally reconstructed PROPELLER images using density compensation demonstrates the advantages of PICO by reducing streaks artifacts and high-spatial-frequency noise on human images in vivo.

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