Nie, L orcid.org/0000-0002-5796-907X, Carpenter, TM, Clegg, HR et al. (3 more authors) (2020) Reducing Dark Region Artifacts in Short-Lag Spatial Coherence (SLSC) Beamforming by Coherence Filtering of the Aperture-Domain Data. In: Proceedings of the 2020 IEEE International Ultrasonics Symposium (IUS). 2020 IEEE International Ultrasonics Symposium (IUS), 07-11 Sep 2020, Las Vegas, NV, USA. IEEE ISBN 978-1-7281-5449-7
Abstract
The short-lag spatial coherence (SLSC) beamformer measures the accumulated similarity of echoes, received by individual transducer elements as a function of spatial separation. It proved beneficial in suppressing incoherent clutter to improve detectability of hypoechoic and anechoic targets. However, with focused beams spatial coherence of backscattered echoes drops significantly away from the focal depth, where dark region artifacts occur due to high-level off-axis interference, reducing the effective depth-of-field when using SLSC. This study aimed to suppress this artificial dropout and keep the image uniformity through depths by filtering the aperture-domain data.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020, IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Robotics, Autonomous Systems & Sensing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 20 Nov 2020 14:55 |
Last Modified: | 16 Feb 2021 22:02 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/ius46767.2020.9251674 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:168197 |