Evidence map›Paper›PMID 37342697›Full record

ArticleBiomedical optics express2023

Adaptive window space direction laser speckle contrast imaging to improve vascular visualization.

Guang Han, De Li, Jiwei Wang, Qianbei Guo, Jixin Yuan, Ruijuan Chen, Jinhai Wang, Huiquan Wang, Jun Zhang

Open access · goldAbstract read
In one paragraph

Article in Biomedical optics express, 2023. 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
3.2field-weighted citation impact, top 8% of its field
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, 18 citations in OpenAlex.

  1. Article
  2. Studies ofJournal of biomedical optics · 2025
    Article
  3. 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

9 authors at 1 institution in 1 country.

Guang HanSchool of life Sciences, Tiangong University, Tianjin, 300387, China.
De LiSchool of life Sciences, Tiangong University, Tianjin, 300387, China.ORCID https://orcid.org/0000-0003-3003-6162
Jiwei WangDepartments of Neurosurgery, Tianjin Huanhu Hospital, Tianjin Key Laboratory of Cerebral Vascular and Neurodegenerative Diseases, Tianjin, 300350, China.
Qianbei GuoSchool of Electrical and Electronic Engineering, Tiangong University, Tianjin 300387, China.
Jixin YuanSchool of life Sciences, Tiangong University, Tianjin, 300387, China.
Ruijuan ChenSchool of life Sciences, Tiangong University, Tianjin, 300387, China.
Jinhai WangSchool of life Sciences, Tiangong University, Tianjin, 300387, China.ORCID https://orcid.org/0000-0003-0789-2980
Huiquan WangSchool of life Sciences, Tiangong University, Tianjin, 300387, China.
Jun ZhangSchool of life Sciences, Tiangong University, Tianjin, 300387, China.ORCID https://orcid.org/0000-0002-3839-8937
Tiangong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Vascular visualization is crucial in monitoring, diagnosing, and treating vascular diseases. Laser speckle contrast imaging (LSCI) is widely used for imaging blood flow in shallow or exposed vessels. However, traditional contrast computation using a fixed-sized sliding window introduces noise. In this paper, we propose dividing the laser speckle contrast image into regions and using the variance criterion to extract pixels more suitable for the corresponding regions for calculation, and changing the shape and size of the analysis window at the vascular boundary regions. Our results show that this method has a higher noise reduction and better image quality in deeper vessel imaging, revealing more microvascular structure information.

Identifiers

PMID37342697
PMCPMC10278620
OpenAlexW4378233531

What Socratic holds

Textmetadata
Read underepoch 390

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 Socratic graph.