TY - JOUR
AU - Pelc, Norbert J
AB - Many imaging experiments involve acquiring a time series of images. To improve imaging speed, several "data-sharing" methods have been proposed, which collect one (or a few) high-resolution reference(s) and a sequence of reduced data sets. In image reconstruction, two methods, known as "Keyhole" and reduced-encoding imaging by generalized-series reconstruction (RIGR), have been used. Keyhole fills in the unmeasured high-frequency data simply with those from the reference data set(s), whereas RIGR recovers the unmeasured data using a generalized series (GS) model, of which the basis functions are constructed based on the reference image(s). This correspondence presents a fast algorithm (and two extensions) for GS-based image reconstruction. The proposed algorithms have the same computational complexity as the Keyhole algorithm, but are more capable of capturing high-resolution dynamic signal changes.
TI - Fast algorithms for GS-model-based image reconstruction in data-sharing Fourier imaging.
JF - IEEE transactions on medical imaging
DO - 10.1109/TMI.2003.815896
DA - 2003-12-04
UR - https://www.deepdyve.com/lp/pubmed/fast-algorithms-for-gs-model-based-image-reconstruction-in-data-LlG6t8YEZQ
SP - 1026
EP - 30
VL - 22
IS - 8
DP - DeepDyve
ER -