Compressive Imaging with Spatial Coding Masks on Low Number of Elements

An Emulation Study

Conference paper (2022)

Authors

Yuyang Hu Erasmus MC
Michael Brown Erasmus MC
D. Doğan Signal Processing Systems - EEMCS
G.J.T. Leus Signal Processing Systems - EEMCS
P. Kruizinga Erasmus MC
Johannes G. Bosch Erasmus MC
Research Group
Signal Processing Systems (EEMCS) (TU Delft)
Copyright: © 2022 Yuyang Hu, Michael Brown, D. Doğan, G.J.T. Leus, P. Kruizinga, Antonius F.W. Van Der Steen, Johannes G. Bosch
DOI
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https://doi.org/10.1109/IUS54386.2022.9957699
Simulation Image reconstruction Carotid artery Compressive imaging Matched filtering
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Published Date

2022

Language

English

Reuse Rights

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Microelectronics

Research Group

Signal Processing Systems

Abstract

We intend to develop an ultrasound compressive imaging device to perform carotid artery (CA) function and flow monitoring/imaging by using just a few single element transducers equipped with spatial coding masks. The spatially unique impulse responses can be exploited in compressive reconstructions. To explore the potential of different configurations, in this study we emulated such a device using a linear array system. We combined its elements with individual digital delays into a small number of groups. The results suggest our spatial coding mask approach based on reconstructions regularized with a least squares method has potential for CA monitoring with only 10 to 12 sensors.