title: 4D MR phase and magnitude segmentations with GPU parallel computing.
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.
authors.affiliation: Department of Physics and Astronomy, University of Manitoba, Winnipeg, MB R3T 2 N2, Canada. Electronic address: rob.bergen@gmail.com.
authors.forename: Robert V
authors.initials: RV
authors.lastname: Bergen
authors.affiliation: Department of Radiology, University of Manitoba, Winnipeg, MB R3T 2 N2, Canada; Medical Devices, National Research Council Canada, Winnipeg, MB R3B 1Y6, Canada.
authors.forename: Hung-Yu
authors.initials: HY
authors.lastname: Lin
authors.affiliation: Department of Physics, University of Winnipeg, Winnipeg, MB R3B 2E9, Canada.
authors.forename: Murray E
authors.initials: ME
authors.lastname: Alexander
authors.affiliation: Department of Physics and Astronomy, University of Manitoba, Winnipeg, MB R3T 2 N2, Canada; Department of Physics, University of Winnipeg, Winnipeg, MB R3B 2E9, Canada.
authors.forename: Christopher P
authors.initials: CP
authors.lastname: Bidinosti
mesh_terms: D000465:Algorithms; D001011:Aorta / Q000473:pathology*; D003196:Computer Graphics; D003952:Diagnostic Imaging; D006801:Humans; D007091:Image Processing, Computer-Assisted; D016018:Least-Squares Analysis; D008279:Magnetic Resonance Imaging; D016011:Normal Distribution; D015203:Reproducibility of Results; D012984:Software; D014584:User-Computer Interface
keywords: 4D; Aorta; GPU; Parallel computing; Phase-contrast; Segmentation