Abstract：
:The increasing size and number of data sets of large four dimensional (three spatial, one temporal) magnetic resonance (MR) cardiac images necessitates efficient segmentation algorithms. Analysis of phase-contrast MR images yields cardiac flow information which can be manipulated to produce accurate segmentations of the aorta. Phase contrast segmentation algorithms are proposed that use simple mean-based calculations and least mean squared curve fitting techniques. The initial segmentations are generated on a multi-threaded central processing unit (CPU) in 10 seconds or less, though the computational simplicity of the algorithms results in a loss of accuracy. A more complex graphics processing unit (GPU)-based algorithm fits flow data to Gaussian waveforms, and produces an initial segmentation in 0.5 seconds. Level sets are then applied to a magnitude image, where the initial conditions are given by the previous CPU and GPU algorithms. A comparison of results shows that the GPU algorithm appears to produce the most accurate segmentation.
journal_name
Magn Reson Imagingjournal_title
Magnetic resonance imagingauthors
Bergen RV,Lin HY,Alexander ME,Bidinosti CPdoi
10.1016/j.mri.2014.08.019subject
Has Abstractpub_date
2015-01-01 00:00:00pages
134-45issue
1eissn
0730-725Xissn
1873-5894pii
S0730-725X(14)00250-1journal_volume
33pub_type
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