Paper Info
Title
Compressed Digital Beamformer with asynchronous sampling for ultrasound imaging
Abstract
The traditional Nyquist sampling architecture does not provide a feasible solution in a large multi-channel ultrasound imaging system. The main issues are the huge data volume after the analog-to-digital interface, high power consumption, and circuit complexity at both the front-end and mid-end. This paper presents a Compressed Digital Beamformer (CDB) framework for the design of an ultrasound imaging system with a large transducer array (≥ 1024) operating at a moderate carrier frequency (≥ 5 MHz). Simulations demonstrate that the proposed CDB framework achieves a Compression Ratio (CR) of 0.1 and Mean Square Error (MSE) of -27.7 dB with 4 quantization bits.
Year
DOI
Venue
2013
10.1109/ICASSP.2013.6637811
ICASSP
Keywords
Field
DocType
ultrasound imaging system design,total variation,compression ratio,asynchronous sampling,power consumption,mean square error,part-time randomization,quantisation (signal),cdb framework,data compression,biomedical ultrasonics,nyquist sampling architecture,data volume,array signal processing,multichannel ultrasound imaging system,mse,image sampling,carrier frequency,compressed sensing,compressed digital beamformer,circuit complexity,transducer array,ultrasonic transducer arrays,ultrasound beamforming,quantization bits,cr,medical image processing,mean square error methods,analog-to-digital interface,imaging,image reconstruction,transducers
Transducer,Computer science,Ultrasound imaging,Mean squared error,Electronic engineering,Artificial intelligence,Nyquist–Shannon sampling theorem,Pattern recognition,Circuit complexity,Speech recognition,Compression ratio,Quantization (signal processing),Data compression
Conference
ISSN
Citations 
PageRank 
1520-6149
4
0.46
References 
Authors
10
5
Name
Order
Citations
PageRank
Jun Zhou150.81
Yong He240.46
Mohan Chirala340.46
Brian M. Sadler43179286.72
Sebastian Hoyos523429.24