Evidence map›Paper›PMID 36268473›Full record

ArticleJournal of computational design and engineering2022

A novel design framework of synthetic radial aperture focusing for volumetric transrectal ultrasound imaging.

Hyunwoo Song, Jeeun Kang, Emad M Boctor

Abstract read
In one paragraph

Article in Journal of computational design and engineering, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Hyunwoo SongDepartment of Computer Science, Whiting School of Engineering, Johns Hopkins University, Baltimore, Maryland 21218, USA.
Jeeun KangLaboratory for Computational Sensing and Robotics, Whiting School of Engineering, Johns Hopkins University, Baltimore, Maryland 21218, USA.ORCID https://orcid.org/0000-0001-6678-2744
Emad M BoctorDepartment of Computer Science, Whiting School of Engineering, Johns Hopkins University, Baltimore, Maryland 21218, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this paper, we present a novel design framework of synthetic radial aperture focusing for three-dimensional (3D) transrectal ultrasound imaging (TRUS-rSAF), in which multiple transmittance/reception events at different scanning angles are synthesized to reconstruct a radial plane in the target volume, securing high spatial resolution and texture uniformity. A theory-based design approach has not been available to push the envelope of the 3D rSAF technique. Herein, a closed-form analytical description of the TRUS-rSAF method is presented for the first time, effectively delineating spatial resolution and grating lobe positions in the radial dimension of a TRUS transducer. We demonstrate a solid optimization workflow based on the theoretical foundation to improve its spatiotemporal resolution, grating lobe artifacts, and signal-to-noise ratio. A specific design criterion was considered to outperform a clinical 3D TRUS imaging as a reference (TRUS-REF), where each radial plane is reconstructed with a single transmittance/reception event using a motorized actuator. The optimized TRUS-rSAF method significantly enhanced spatial resolution up to 50% over the TRUS-REF method while providing clinically effective temporal resolution (2-8 volume/sec) with negligible grating lobe artifacts. The results indicate that the proposed design approach would enable a novel TRUS imaging solution in clinics.

Indexed as

analytical optimizationsynthetic aperture focusingtransrectal ultrasoundultrasound beamformingvolumetric imaging

Identifiers

PMID36268473
PMCPMC9563629

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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.