2016 JRNL PP T. Küstner - 1.pdf
Terbatas  Irwan Sofiyan
» Gedung UPT Perpustakaan
Terbatas  Irwan Sofiyan
» Gedung UPT Perpustakaan
A Cartesian subsampling scheme is proposed incorporating
the idea of PF acquisition and variable-density Poisson
Disc (vdPD) subsampling by redistributing the sampling space
onto a smaller region aiming to increase k-space sampling
density for a given acceleration factor. Especially the normally
sparse sampled high-frequency components benefit from this
sampling redistribution, leading to improved edge delineation.
The prospective subsampled and compacted k-space can be
reconstructed by a seamless combination of a CS-algorithm with
a Hermitian symmetry constraint accounting for the missing
part of the k-space. This subsampling and reconstruction scheme
is called Compressed Sensing Partial Subsampling (ESPReSSo)
and was tested on in-vivo abdominal MRI datasets. Different
reconstruction methods and regularizations are investigated and
analyzed via global (intensity-based) and local (region-of-interest
and line evaluation) image metrics, to conclude a clinical feasible
setup. Results substantiate that ESPReSSo can provide improved
edge delineation and regional homogeneity for multidimensional
and multi-coil MRI datasets and is therefore useful in applications
depending on well-defined tissue boundaries, such as image
registration and segmentation or detection of small lesions in
clinical diagnostics.