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.
This abstract and the presentation materials are available to members only;
a login is required.
Join Here
