Evidence map›Paper›PMID 31251180›Full record

ArticleIEEE transactions on ultrasonics, ferroelectrics, and frequency control2019

Computationally Efficient Implementation of Aperture Domain Model Image Reconstruction.

Kazuyuki Dei, Siegfried Schlunk, Brett Byram

Abstract read
In one paragraph

Article in IEEE transactions on ultrasonics, ferroelectrics, and frequency control, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. A Real-Time, GPU-Based Implementation of Aperture Domain Model Image REconstruction.IEEE transactions on ultrasonics, ferroelectrics, and frequency control · 2021
    Article
  3. Iterative Model-Based Beamforming for High Dynamic Range Applications.IEEE transactions on ultrasonics, ferroelectrics, and frequency control · 2021
    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.

Kazuyuki Dei
Siegfried Schlunk
Brett Byram

Funding

Suppression and Analysis of Ultrasonic Clutter During Liver Focal Lesion BiopsyR01EB020040 · NIBIB · VANDERBILT UNIVERSITY · PI BYRAM, BRETT C · 2016 to 2019
$1.3M
Parallel Computer with High Memory NodesS10OD016216 · OD · VANDERBILT UNIVERSITY · PI PISTON, DAVID W · 2013 to 2013
$598k
NIBIB NIH HHS R01 EB020040NIH HHS S10 OD016216
6 · The paper itself

Abstract

Aperture domain model image reconstruction (ADMIRE) is a useful tool to mitigate ultrasound imaging artifacts caused by acoustic clutter. However, its lengthy run-time impairs its usefulness. To overcome this drawback, we evaluated the reduced model methods with otherwise similar performance to ADMIRE. We also assessed other approaches to speed up ADMIRE, including the use of different levels of short-time Fourier transform (STFT) window overlap and examining the degrees of freedom of the model fit. In this study, we conducted an analysis of the reduced models, including those using Gram-Schmidt orthonormalization (GSO), singular value decomposition (SVD), and independent component analysis (ICA). We evaluated these reduced models using the data from simulations, experimental phantoms, and in vivo liver scans. We then tested ADMIRE's performance using full, GSO, SVD, and ICA-fourth-order blind identification (ICA-FOBI) models. The results from simulations, experimental phantoms, and in vivo data indicate that a model reduced using the ICA-FOBI method is the most promising for accelerating ADMIRE implementation. In the in vivo liver data, the improvements in contrast relative to delay-and-sum (DAS) using a full model, GSO, SVD, and ICA-FOBI models are 6.29 ± 0.25 dB, 11.88 ± 0.90 dB, 9.01 ± 0.67 dB, and 6.36 ± 0.27 dB, respectively; whereas, the contrast-to-noise ratio (CNR) improvement values in the same order are 0.04 ± 0.06 dB, -1.70 ± 0.17 dB, -1.51 ± 0.19 dB, and 0.12 ± 0.07 dB, respectively. The implementation of ADMIRE using the reduced model methods can decrease ADMIRE's computational complexity over three orders of magnitude. The use of a 50% STFT window overlap reduces ADMIRE's serial run time by more than one order of magnitude without any remarkable loss of image quality, when compared to the use of a 90% window overlap used previously. Based on these findings, a combination of the ICA-FOBI model and the use of a 50% STFT window overlap makes the ADMIRE algorithm more computationally efficient.

Indexed as

Signal Processing, Computer-AssistedAlgorithmsArtifactsHumansImage Processing, Computer-AssistedLiverPhantoms, ImagingUltrasonography

Identifiers

PMID31251180
PMCPMC6800222

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.