Image analysis – Image transformation or preprocessing – Fourier transform
Reexamination Certificate
2004-06-28
2009-02-03
Le, Brian Q (Department: 2624)
Image analysis
Image transformation or preprocessing
Fourier transform
C382S131000, C382S132000
Reexamination Certificate
active
07486839
ABSTRACT:
SENSitivity Encoding (SENSE) has demonstrated potential for significant scan time reduction using multiple receiver channels. SENSE reconstruction algorithms for non-uniformly sampled data proposed to date require relatively high computational demands. A Projection Onto Convex Sets (POCS)-based SENSE reconstruction method (POCSENSE) has been recently proposed as an efficient reconstruction technique in rectilinear sampling schemes. POCSENSE is an iterative algorithm with a few constraints imposed on the acquired data sets at each iteration. Although POCSENSE can be readily performed on rectilinearly acquired k-space data, it is difficult to apply to non-uniformly acquired k-space data. Iterative Next Neighbor re-Gridding (INNG) algorithm is a recently proposed new reconstruction method for non-uniformly sampled k-space data. The POCSENSE algorithm can be extended to non-rectilinear sampling schemes by using the INNG algorithm. The resulting algorithm (POCSENSINNG) is an efficient SENSE reconstruction algorithm for non-uniformly sampled k-space data, taking into account coil sensitivities.
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Duerk Jeffrey L.
Moriguchi Hisamoto
Case Western Reserve University
Le Brian Q
Tsai Tsung-Yin
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