Extracting Salient Features From Less Data via `1-Minimization
نویسندگان
چکیده
MRI (magnetic resonance imaging) is a widely used medical imaging modality that creates an image from scanned data that are essentially the Fourier coefficients of this image. A typical abdominal scan may take around 90 minutes. Can we reduce this time to 30 minutes by using one third of the Fourier coefficients, while maintaining image quality? In this article, we hope to convince the reader that such reductions are achievable through a new and promising approach called compressive sensing (or compressed sensing). The main computational engine that drives compressive sensing is `1-related minimization algorithms.
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تاریخ انتشار 2008