Evidence map›Paper›PMID 42735169›Full record

ArticleIEEE transactions on ultrasonics2026

Spatial Coherence-Based Sound Speed Estimation in Plane Wave Ultrasound Imaging.

Jiaxin Zhang, Yunlong Zhu, Muyinatu A Lediju Bell

Abstract read
In one paragraph

Article in IEEE transactions on ultrasonics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Jiaxin Zhang
Yunlong Zhu
Muyinatu A Lediju Bell

Funding

Minimizing Uncertainty in Breast Ultrasound Imaging with Real-Time Coherence-Based BeamformingR01EB032960 · NIBIB · JOHNS HOPKINS UNIVERSITY · PI BELL, MUYINATU A. LEDIJU · 2022 to 2025
$1.6M
NIBIB NIH HHS R01 EB032960
6 · The paper itself

Abstract

A globally constant sound speed of 1540 m/s is often assumed when beamforming ultrasound images, despite variations in tissue properties that lead to heterogeneous sound speeds. As a result, the majority of local sound speeds are often misrepresented, which degrades image quality, resulting in inaccurate target depths, sizes, and shapes, thus reducing the overall effectiveness of diagnostic and interventional ultrasound imaging. In this article, we introduce a spatial coherence-based approach to estimate local sound speeds within and surrounding coherent and incoherent targets in ultrasound images acquired with multiple plane wave transmissions. Ultrasound data with known ground-truth sound speeds were simulated. "Optimal" sound speeds produced the lowest possible lateral full-width at half maximum (FWHM) of point targets, the lowest possible contrast of hypoechoic or anechoic targets, or the highest possible contrast of hyperechoic targets, serving as the ground-truth sound speed for experimental data. With our proposed method, sound speeds achieved 99.68-100% agreement with the simulated ground-truth value. When benchmarked against the optimal sound speeds, our coherence-based method yielded 0.58% and 0.56% mean deviations from optimal sound speeds in tissue-mimicking phantom data and in vivo breast data, respectively, whereas a speckle brightness maximization approach produced larger deviations of 2.50% and 3.41%, respectively. Qualitatively, B-mode images created with coherence-based sound speeds improved lateral FWHM, enhanced contrast, reduced acoustic clutter, better delineated target boundaries, and better defined speckle patterns. These results promise to improve accuracy and enhance the effectiveness of diagnostic and interventional ultrasound procedures.

Indexed as

Image Processing, Computer-AssistedAlgorithmsComputer SimulationHumansPhantoms, ImagingUltrasonography

Identifiers

PMID42735169
PMCPMC13576383

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.