Compressive Sensing Application in Large Scale Ultrasound Medicine Imaging
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Ying Li, Siyuan Wen
We use a compressed sensing method to store and recover the large-scale ultrasound medicine radio-frequency (RF) signals generated from plane wave (PW). We investigate performance of reconstruction on different ultrasound post-beamformed data when performing compressed sensing with fewer measurement data. Reconstruction is performed using convex optimization algorithm. For a single channel sequence, the iteration processing is fast even not more than 20 times. RF data from Field II simulation of a phantoms and the plane-wave imaging challenge in medical ultrasound (PICMUS) data sets. Using the 50% measurement data, we get a closed approximate channel data. In term of mean-square-error, reconstruction on RF data performs well.
Compressed sensing, Ultrasound medicine imaging, Plane wave