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High-resolution image reconstruction for portable ultrasound imaging devices.

Authors :
Wang, Ruoyao
Fang, Zhenghan
Gu, Jiaqi
Guo, Yi
Zhou, Shicong
Wang, Yuanyuan
Chang, Cai
Yu, Jinhua
Source :
EURASIP Journal on Advances in Signal Processing; 11/27/2019, Vol. 2019 Issue 1, pN.PAG-N.PAG, 1p
Publication Year :
2019

Abstract

Pursuing better imaging quality and miniaturizing imaging devices are two trends in the current development of ultrasound imaging. While the first one leads to more complex and expensive imaging equipment, poor image quality is a common problem of portable ultrasound imaging systems. In this paper, an image reconstruction method was proposed to break through the imaging quality limitation of portable devices by introducing generative adversarial network (GAN) model into the field of ultrasound image reconstruction. We combined two GAN generator models, the encoder-decoder model and the U-Net model to build a sparse skip connection U-Net (SSC U-Net) to tackle this problem. To produce more realistic output, stabilize the training procedure, and improve spatial resolution in the reconstructed ultrasound images, a new loss function which combines adversarial loss, L1 loss, and differential loss was proposed. Three datasets including 50 pairs of simulation, 40 pairs of phantom, and 72 pairs of in vivo images were used to evaluate the reconstruction performance. Experimental results show that our SSC U-Net is able to reconstruct ultrasound images with improved quality. Compared with U-Net, our SSC U-Net is able to preserve more details in the reconstructed images and improve full width at half maximum (FWHM) of point targets by 3.23%. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
16876172
Volume :
2019
Issue :
1
Database :
Complementary Index
Journal :
EURASIP Journal on Advances in Signal Processing
Publication Type :
Academic Journal
Accession number :
139882333
Full Text :
https://doi.org/10.1186/s13634-019-0649-x