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The greedy approach has the benefit of fast reconstruction.
We also propose a compressed maximum matching select (CMMS) algorithm for fast reconstruction of the signal.
Image reconstruction was performed on a quad-core PC running a fast reconstruction algorithm [31].
As a result, the conventional algorithms of projection computed tomography can be used for fast reconstruction of diffuse optical images.
The Lorentzian-based Iterative Hard Thresholding (LIHT) approach is proposed as the fast reconstruction method in [22].
However, future evolutions might consider a transparent integration with Unix HPC to perform a fast reconstruction at the facility.
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Model-based reconstruction methods have three benefits: (1) the reduction of the number of measurements, (2) the increase in robustness, and (3) the faster reconstruction.
The reconstruction algorithm plays a key role to the construction of three-dimensional ultrasound volume data with higher image quality and faster reconstruction speed.
Such a representation may have various advantages over (15), e.g., allowing for a faster reconstruction procedure, while being completely equivalent in terms of the ZL property.
Also, MIMP has a reasonable relatively faster reconstruction speed by introducing the matching strategies of greedy algorithm and using the edge saliency as a prior knowledge.
Thus, it is unlikely that CS would find widespread application in data compression, as there are methods with faster reconstruction, e.g., vector quantization (VQ) [3] and floating-point array compression [4].
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