Evidence map›Paper›PMID 36366256›Full record

ArticleSensors (Basel, Switzerland)2022

Design and Implementation of Embedded-Based Vein Image Processing System with Enhanced Denoising Capabilities.

Jongwon Lee, Incheol Jeong, Kapyol Kim, Jinsoo Cho

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
1.0field-weighted citation impact, top 25% 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

2 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.

  1. Pooled it
  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 at 1 institution in 1 country.

Jongwon LeeDepartment of Computer Engineering, Gachon University Global Campus, Seongnam 13120, Korea.
Incheol JeongDepartment of Computer Engineering, Gachon University Global Campus, Seongnam 13120, Korea.
Kapyol KimDepartment of Computer Engineering, Gachon University Global Campus, Seongnam 13120, Korea.
Jinsoo ChoDepartment of Computer Engineering, Gachon University Global Campus, Seongnam 13120, Korea.
Gachon University · KR

Funding

Gachon University GCU-2019-0795National Research Foundation of Korea(NRF) No. 2019R1F1A1057757
6 · The paper itself

Abstract

In general, it is very difficult to visually locate blood vessels for intravenous injection or surgery. In addition, if vein detection fails, physical and mental pain occurs to the patient and leads to financial loss in the hospital. In order to prevent this problem, NIR-based vein detection technology is developing. The proposed study combines vein detection and digital hair removal to eliminate body hair, a noise that hinders the accuracy of detection, improving the performance of the entire algorithm by about 10.38% over existing systems. In addition, as a result of performing venous detection of patients without body hair, 5.04% higher performance than the existing system was detected, and the proposed study results were verified. It is expected that the use of devices to which the proposed study is applied will provide more accurate vascular maps in general situations.

Indexed as

AlgorithmsImage Processing, Computer-AssistedHumansSignal-To-Noise Ratiodigital hair removalembedded systemimage processingvein detectionvein projection

Identifiers

PMID36366256
PMCPMC9656323
OpenAlexW4308392024

What OpenQuestion holds

Textmetadata
LicenceCC BY
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 OpenQuestion graph.