Evidence map›Paper›PMID 42779911›Full record

ArticleArXiv2026

Lens-Aware Differentiable Beamforming for In Vivo Distributed Aberration Correction with Curvilinear Transducers.

Benjamin N Frey, Robin van Velzen, Hoda S Hashemi, Samuel Beuret, Martin Schneider, Alice C Fan, Christian R Hoerner, Aya Kamaya, Sergio J Sanabria, Jeremy J Dahl

Abstract readPreprint
PubMed Full text at PMC
In one paragraph

Article in ArXiv, 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
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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

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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

10 authors.

Benjamin N FreyDept. of Applied Physics, Stanford University, Stanford, CA, USA.
Robin van VelzenDept. of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands.
Hoda S HashemiDept. of Radiology, Stanford University, Stanford, CA, USA.
Samuel BeuretDept. of Radiology, Stanford University, Stanford, CA, USA.
Martin SchneiderDept. of Radiology, Stanford University, Stanford, CA, USA.
Alice C FanDept. of Radiology, Stanford University, Stanford, CA, USA.
Christian R HoernerDept. of Radiology, Stanford University, Stanford, CA, USA.
Aya KamayaDept. of Radiology, Stanford University, Stanford, CA, USA.
Sergio J SanabriaDept. of Radiology, Stanford University, Stanford, CA, USA.
Jeremy J DahlDept. of Radiology, Stanford University, Stanford, CA, USA.

Funding

Improving Liver Ultrasound Image Quality in Difficult-to-Image PatientsR01EB027100 · NIBIB · STANFORD UNIVERSITY · PI DAHL, JEREMY · 2020 to 2023
$2.3M
NIBIB NIH HHS R01 EB027100
6 · The paper itself

Abstract

We previously introduced ultrasound autofocusing, an iterative model-based aberration correction technique that estimates local sound speed and incorporates it into beamforming to correct image distortion from heterogeneous media. In this work, we extend ultrasound autofocusing to curvilinear arrays and introduce advancements to the underlying model. A differentiable bent-ray tracing approach accounts for refraction through the transducer lens, while a new adaptive-grid initialization accounts for changes in speckle position with sound speed. The method is validated in silico and in calibrated sound speed phantoms. Our distributed aberration-correction method is then applied to a first large-scale in vivo evaluation comprising 313 liver acquisitions from 76 high-BMI human subjects. In images containing anechoic regions, contrast and CNR improved by 1.38±1.60 dB (+18.0%) and 0.09±0.14 (+10.2%), respectively. Improvements were also observed in speckle brightness (+20.3%), coherence factor (+13.1%), lag-one coherence (+2.7%), common-midpoint correlation coefficient (+0.7%), and common-midpoint phase error (-9.1%; lower is better), with all metric improvements statistically significant. Target structure and visibility also improved significantly. These results demonstrate the potential of ultrasound autofocusing for clinically applicable distributed aberration correction.

Indexed as

aberration correctionacoustic imagingdifferentiable beamformingultrasound autofocusing

Identifiers

PMID42779911
PMCPMC13596618

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.