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A dynamic generalized coherence factor for side lobe suppression in ultrasound imaging.

Authors :
Wang Y
Peng H
Zheng C
Han Z
Qiao H
Source :
Computers in biology and medicine [Comput Biol Med] 2020 Jan; Vol. 116, pp. 103522. Date of Electronic Publication: 2019 Nov 15.
Publication Year :
2020

Abstract

Coherence-based weighting techniques have been widely studied to weight beamsummed data to improve image quality in ultrasound imaging. Although generalized coherence factor (GCF) enhances the robustness of coherence factor (CF) with preserved speckle pattern by including some incoherent components, the side lobe suppression performance is insufficient due to constant cut-off frequency M <subscript>0</subscript> . To address this problem, we introduced in this paper a dynamic GCF method, referred to as DGCF-C, based on the amplitude standard deviation and the convolution output of aperture data. The cut-off frequency is adaptively selected for GCF at each imaging point using the amplitude standard deviation of aperture data. Moreover, the convolution output of aperture data is used to calculate the dynamic GCF. The proposed method is evaluated in simulation and tissue-mimicking phantom studies. The image quality was analyzed in terms of resolution, contrast ratio (CR), generalized contrast-to-noise ratio (GCNR), speckle signal-to-noise ratio (sSNR), and signal-to-noise ratio (SNR). The results demonstrate that DGCF-C (M <subscript>max</subscript> =2) achieves mean resolution improvements of 35.1% in simulation, and 32.6% in experiment, compared with GCF (M <subscript>0</subscript> =1). Moreover, DGCF-C (M <subscript>max</subscript> =4) outperforms GCF (M <subscript>0</subscript> =2) with an average GCNR improvement of 13.5% and an average sSNR improvement of 15.2%, which indicates the better-preservation of speckle.<br /> (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Details

Language :
English
ISSN :
1879-0534
Volume :
116
Database :
MEDLINE
Journal :
Computers in biology and medicine
Publication Type :
Academic Journal
Accession number :
31739004
Full Text :
https://doi.org/10.1016/j.compbiomed.2019.103522