Evidence map›Paper›PMID 34113219›Full record

ArticleMolecular imaging2021

A Photoacoustic Imaging Algorithm Based on Regularized Smoothed L

Xueyan Liu, Limei Zhang, Yining Zhang, Lishan Qiao

Abstract read
In one paragraph

Article in Molecular imaging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

4 authors.

Xueyan LiuDepartment of Mathematics Science, Liaocheng University, Shandong 252000, China.ORCID 0000-0003-4634-5680
Limei ZhangDepartment of Mathematics Science, Liaocheng University, Shandong 252000, China.
Yining ZhangDepartment of Mathematics Science, Liaocheng University, Shandong 252000, China.
Lishan QiaoDepartment of Mathematics Science, Liaocheng University, Shandong 252000, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The recently emerging technique of sparse reconstruction has received much attention in the field of photoacoustic imaging (PAI). Compressed sensing (CS) has large potential in efficiently reconstructing high-quality PAI images with sparse sampling signal. In this article, we propose a CS-based error-tolerant regularized smooth L0 (ReSL0) algorithm for PAI image reconstruction, which has the same computational advantages as the SL0 algorithm while having a higher degree of immunity to inaccuracy caused by noise. In order to evaluate the performance of the ReSL0 algorithm, we reconstruct the simulated dataset obtained from three phantoms. In addition, a real experimental dataset from agar phantom is also used to verify the effectiveness of the ReSL0 algorithm. Compared to three L

Indexed as

Photoacoustic TechniquesAlgorithmsDiagnostic ImagingImage Processing, Computer-AssistedPhantoms, Imaging

Identifiers

PMID34113219
PMCPMC8187066

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.