Estimation of Flexible Ultrasound Array Shape Using Phase Coherence

An algorithm to estimate the shape of a flexible ultrasound array transducer from backscattered ultrasound signals is presented. The algorithm exploits the phase variation across the receive channels to compute an array shape focusing criterion related to the array shape. This metric quantifies the phase variation at a set of spatial positions and the correct array shape is identified by the maximum of this metric. Its practical implementation is presented in the context of an overall shape estimation workflow using both simulated and experimental data. Using a 128-element, 2.5 MHz centre frequency flexible array transducer, the channel data of a tissue-mimicking phantom were recorded. The beam response was calibrated with respect to a known array shape facilitating quick and accurate shape estimation from these data. The algorithm was demonstrated to accurately predict the array shape corresponding to a root mean square error of the estimated element locations within 0.18 $\lambda$ and 0.4 $\lambda$ using simulated and experimental data respectively. This was performed using data recorded from a single transmit event and in a calculation time of approximately 300 ms.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Biomedical Engineering
Published
2024-12-12
DOI
https://doi.org/10.1109/tbme.2024.3516875
Citations
3
Primary Topic
Ultrasound Imaging and Elastography
Type
article
Field-Weighted Citation Impact
1.21
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Estimation of Flexible Ultrasound Array Shape Using Phase Coherence

Marcus Ingram, Jan D’hooge
3 citations
IEEE Transactions on Biomedical Engineering
Ultrasound Imaging and Elastography
1.21
article

Estimation of Flexible Ultrasound Array Shape Using Phase Coherence

Marcus Ingram, Jan D’hooge
article en
3 citations

Abstract

An algorithm to estimate the shape of a flexible ultrasound array transducer from backscattered ultrasound signals is presented. The algorithm exploits the phase variation across the receive channels to compute an array shape focusing criterion related to the array shape. This metric quantifies the phase variation at a set of spatial positions and the correct array shape is identified by the maximum of this metric. Its practical implementation is presented in the context of an overall shape estimation workflow using both simulated and experimental data. Using a 128-element, 2.5 MHz centre frequency flexible array transducer, the channel data of a tissue-mimicking phantom were recorded. The beam response was calibrated with respect to a known array shape facilitating quick and accurate shape estimation from these data. The algorithm was demonstrated to accurately predict the array shape corresponding to a root mean square error of the estimated element locations within 0.18 $\lambda$ and 0.4 $\lambda$ using simulated and experimental data respectively. This was performed using data recorded from a single transmit event and in a calculation time of approximately 300 ms.

IEEE Transactions on Biomedical EngineeringVol. 72(5)
KU Leuven (BE)
Affordable and clean energy
Openalex Percentile: Top 19%
Ultrasound Imaging and Elastography
1.21
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.