Carpenter, TM, Cowell, DMJ orcid.org/0000-0003-0854-542X and Freear, S orcid.org/0000-0001-7858-4155 (2019) Real-Time FIR Filter Equalisation of Analog Front Ends for Soft-Tissue Quantitative Ultrasound. In: IEEE International Ultrasonics Symposium, IUS. 2018 IEEE International Ultrasonics Symposium (IUS), 22-25 Oct 2018, Kobe, Japan. IEEE ISBN 978-1-5386-3425-7
Abstract
A typical ultrasound imaging system analogue front end (AFE) consists of a series of stages, including transmit/receive switch, amplifiers and analog-digital converter (ADC). Each stage will have an impact on the signal in the form of noise, but also in the form of distortion from a frequency-dependent gain profile. This gain response will be applied to any ultrasound echo signal received by the system. This paper highlights the presence of this distortion and proposes a method of identifying the distortion caused by the front end and performing compensation in realtime using per-channel finite-impulse-response (FIR) filters. The University of Leeds Ultrasound Array Research Platform (UARP) was used as a typical example system for which the AFE frequency response was analysed, though any system using integrated analogue front ends will exhibit similar behaviour. The proposed method was used to determine the necessary inverse response filter for the UARP system. With the filter inserted into the digital signal processing path and the resulting frequency response is measured to verify functionality. The presented results demonstrate how digital FIR filters can be used to effectively equalise the gain profile of the AFE in real-time using hardware Finite Impulse Response (FIR) filters within the UARP research system.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019, IEEE. This is an author produced version of a paper published in IEEE International Ultrasonics Symposium, IUS. Uploaded in accordance with the publisher's self-archiving policy. |
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: | 02 Oct 2019 11:13 |
Last Modified: | 25 Jun 2023 22:00 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/ULTSYM.2018.8579691 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:151559 |