Evidence map›Paper›PMID 36059289›Full record

ArticleJournal of biomedical physics & engineering2022

Effects of Beamforming Techniques on Quality of Ultrasound Computed Tomography Images.

Razieh Solgi, Hossein Ghadiri

Abstract read
In one paragraph

Article in Journal of biomedical physics & 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

2 authors.

Razieh SolgiMSc, Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran.
Hossein GhadiriPhD, Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: In body tissues, tumors generally have different speeds of sound (SOS) than normal tissues. In this respect, ultrasound computed tomography (UCT) can generate a cross-sectional SOS map as an innovative ultrasound imaging method. This technique can produce images with a resolution of millimeters and a high signal-to-noise ratio. Objective: This study aimed to improve UCT image quality without increasing breast cancer screening and diagnosis time. Material and Methods: In this analytical study, a ring-shaped UCT breast imaging system was simulated using the K-wave toolbox of MATLAB. The system has a 20 cm diameter and 256 ultrasonic piezoelectrics placed in the ring's circumference. Different beamforming techniques imaged two designed phantoms (i.e., resolution and contrast), and the resolution and contrast to noise ratio (CNR) were calculated. Results: The results of resolution phantom imaging without any beamforming showed that only bars with the value of 0.125 and 0.167 lp/mm were distinguishable, and the 0.1 bars were not recognizable in the imaging. In addition, increasing the number of transmitters led to no noticeable change in resolution for 0.125 and 0.167 lp/mm bars. In all beamforming techniques for imaging the contrast phantom, the CNR parameter up to an object with a diameter of 8 mm increases with increasing diameter without any change. Conclusion: The beamforming technique using three simultaneous transmitters improved the resolution by about 1 mm compared to the normal strategy. In addition to high-contrast images, beamforming with 9 simultaneous transmitters led to a preferable technique.

Indexed as

BeamformingFan Beam Back ProjectionImage Quality EnhancementImage ReconstructionSignal-To-Noise RatioTomographyUltrasonographyUltrasound Computed TomographyUltrasound Imaging

Identifiers

PMID36059289
PMCPMC9395622

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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.