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Fast MRI makes it possible to visualize dynamic biological phenomena and can potentially reduce the cost of diagnostic imaging. Constrained imaging methods such as compressive sense (CS) and optimal lattice sampling (OLS) have proven to be effective for speeding up MRI. In doing so, CS takes advantage of the image sparsity or compressibility and OLS utilizes the known signal/spectrum support. Interestingly,...
Nonlinear spatial encoding fields for magnetic resonance imaging (MRI) hold great promise to improve on the linear gradient approaches. Unlike the linear techniques, the nonlinear encoding leads to a spatially varying signal-to-noise ratio (SNR). This paper demonstrates the possibility to tailor the encoding fields to focus the high SNR areas to a region of interest. To achieve this, a metric is derived...
As imaging, computing, and data storage technologies improve, there is an increasing opportunity for multiscale analysis of three-dimensional datasets (3-D). Such analysis enables, for example, microscale elements of multiple macroscale specimens to be compared throughout the entire macroscale specimen. Spatial comparisons require bringing datasets into co-alignment. One approach for co-alignment...
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