Computer hardware

Ultrasound

Engineering

Biology

Biomedical engineering

Contrast (vision)

Image quality

Telecommunications

Ultrasonic sensor

Computer science

Compression ratio

Scanner

Radiology

Internal combustion engine

Paleontology

Decoding methods

Image (mathematics)

Automotive engineering

Artificial intelligence

Medicine

Channel (broadcasting)

Compressed sensing

Noise (video)

Footprint

Computer vision

Ultrasonics

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 of the front-end electronics with only a minor loss in image quality. We demonstrate an 8-fold receive channel count reduction with a 3.16 dB and 3.64 dB mean absolute error for gallbladder and kidney images, respectively, as well as 7.4% increase in the contrast-to-noise ratio for kidney images and 0.1% loss in the contrast-to noise ratio for gallbladder images, on average. The proposed method may enable a fully portable ultrasonic device with virtually no loss in image quality as compared to a full size clinical scanner to be constructed.

Compressed sensing for reduced hardware footprint in medical ultrasound