PROJECT TITLE :
Enhanced Ultrasound Image Reconstruction Using A Compressive Blind Deconvolution Approach - 2017
Compressive deconvolution, combining compressive sampling and image deconvolution, represents an fascinating possibility to reconstruct enhanced ultrasound images from compressed measurements. The model of compressive deconvolution includes, in addition to the measurement matrix, a 2D convolution operator carrying the data on the system point spread operate which is usually unkown in follow. During this paper, we propose a novel alternating minimization-based mostly optimization theme to invert the resulting linear model, to jointly reconstruct enhanced ultrasound pictures and estimate the point unfold operate. The performance of the strategy is evaluated on both Shepp-Logan phantom and simulated ultrasound information.
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