Development of a Wireless and Near Real-Time 3D Ultrasound Strain Imaging System

Ultrasound elastography is an important medical imaging tool for characterization of lesions. In this paper, we present a wireless and near real-time 3D ultrasound strain imaging system. It uses a 3D translating device to control a commercial linear ultrasound transducer to collect pre-compression a...

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Bibliographic Details
Published in:IEEE transactions on biomedical circuits and systems 2016-04, Vol.10 (2), p.394-403
Main Authors: Chen, Zhaohong, Chen, Yongdong, Huang, Qinghua
Format: Article
Language:English
Subjects:
3D ultrasound
Algorithms
Arrays
Computer Systems
Data Compression
Devices
Elasticity Imaging Techniques - instrumentation
Equipment Design
Estimation
Frames
Humans
Imaging
Imaging, Three-Dimensional - instrumentation
Materials Testing
mechanical scanning
parallel computing
Probes
Radio frequency
Real time
Servers
Strain
strain imaging
Three dimensional
Three-dimensional displays
Ultrasonic imaging
Ultrasound
wireless data transfer
Wireless Technology - instrumentation
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Summary:Ultrasound elastography is an important medical imaging tool for characterization of lesions. In this paper, we present a wireless and near real-time 3D ultrasound strain imaging system. It uses a 3D translating device to control a commercial linear ultrasound transducer to collect pre-compression and post-compression radio-frequency (RF) echo signal frames. The RF frames are wirelessly transferred to a high-performance server via a local area network (LAN). A dynamic programming strain estimation algorithm is implemented with the compute unified device architecture (CUDA) on the graphic processing unit (GPU) in the server to calculate the strain image after receiving a pre-compression RF frame and a post-compression RF frame at the same position. Each strain image is inserted into a strain volume which can be rendered in near real-time. We take full advantage of the translating device to precisely control the probe movement and compression. The GPU-based parallel computing techniques are designed to reduce the computation time. Phantom and in vivo experimental results demonstrate that our system can generate strain volumes with good quality and display an incrementally reconstructed volume image in near real-time.
ISSN:1932-4545
1940-9990
DOI:10.1109/TBCAS.2015.2420117