Compressed sensing for reduced hardware footprint in medical ultrasound
| Autor: | Jovan Mitrovic, Zeljko Ignjatovic, Lynn M. La Pietra, William J. Sehnert, Vikram S. Dogra |
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| Rok vydání: | 2020 |
| Předmět: |
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Acoustics and Ultrasonics Channel (digital image) Computer science Image quality Signal-To-Noise Ratio Kidney 01 natural sciences Noise (electronics) Reduction (complexity) 0103 physical sciences Image Processing Computer-Assisted Humans 010301 acoustics Ultrasonography 010302 applied physics business.industry Gallbladder Signal Processing Computer-Assisted Data Compression Healthy Volunteers Compressed sensing Liver Radio frequency business Algorithms Decoding methods Computer hardware |
| Zdroj: | Ultrasonics. 108:106214 |
| ISSN: | 0041-624X |
| DOI: | 10.1016/j.ultras.2020.106214 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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