Compressed sensing for reduced hardware footprint in medical ultrasound.

Jovan Mitrovic¹, Zeljko Ignjatovic², Lynn La Pietra³, William J Sehnert³, Vikram Dogra⁴

¹Dept of Electrical and Computer Engineering, University of Rochester, Rochester, NY, USA. Electronic address: jovan.mitrovic@rochester.edu.

²Dept of Electrical and Computer Engineering, University of Rochester, Rochester, NY, USA. Electronic address: zeljko.ignjatovic@rochester.edu.

³Carestream Health Inc., Rochester, NY,USA.

⁴Dept of Imaging Sciences, University of Rochester, Rochester, NY, USA.

PubMed DOI

Abstract

In this work, a compressed sensing method to reduce hardware complexity of ultrasound imaging systems is proposed and experimentally verified. We provide clinical evaluation of the method with a possible high compression rates (up to 64 RF signals compressed into a single channel on receive) which uses elastic net estimation for decoding stage. This allows a reduction in size and power consumption…

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