Evidence map›Paper›PMID 38504440›Full record

ArticleSkin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)2024

Correlation analysis between texture features and elasticity of skin hyperspectral images in the near-infrared band.

Juhyun Kim, Onseok Lee

Open access · hybridAbstract read
In one paragraph

Article in Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI), 2024. 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
2.8field-weighted citation impact, top 10% 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, 7 citations in OpenAlex.

  1. Article
  2. Parameter-based transfer learning for severity classification of atopic dermatitis using hyperspectral imaging.Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI) · 2024
    Article
  3. Correlation analysis between texture features and elasticity of skin hyperspectral images in the near-infrared band.Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI) · 2024
    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 at 1 institution in 2 countries.

Juhyun KimDepartment of Software Convergence, Graduate School, Soonchunhyang University, Asan City, Chungnam, Republic of Korea.
Onseok LeeDepartment of Software Convergence, Graduate School, Soonchunhyang University, Asan City, Chungnam, Republic of Korea.
Soonchunhyang University · KR

Funding

BK21 FOUR (Fostering Outstanding Universities for Research) 5199990914048Health Fellowship Foundation 2023National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) 2022R1A2C1010170Soonchunhyang University Research Fund
6 · The paper itself

Abstract

background/purposeSkin elasticity was used to evaluate healthy and diseased skin. Correlation analysis between image texture characteristics and skin elasticity was performed to study the feasibility of assessing skin elasticity using a non-contact method. MATERIALS AND

methodsSkin images in the near-infrared band were acquired using a hyperspectral camera, and skin elasticity was obtained using a skin elastimeter. Texture features of the mean, standard deviation, entropy, contrast, correlation, homogeneity, and energy were extracted from the acquired skin images, and a correlation analysis with skin elasticity was performed.

resultsThe texture features, and skin elasticity of skin images in the near-infrared band had the highest correlation on the side of eye and under of arm, and the mean and correlation were features of texture suitable for distinguishing skin elasticity according to the body part.

conclusionIn this study, we performed elasticity and correlation analyses for various body parts using the texture characteristics of skin hyperspectral images in the near-infrared band, confirming a significant correlation in some body parts. It is expected that this will be used as a cornerstone of skin elasticity evaluation research using non-contact methods.

Indexed as

SkinElasticityHumanscorrelation analysishyperspectral imagingNIRnoncontactskin elasticitytexture analysis

Identifiers

PMID38504440
PMCPMC10951415
OpenAlexW4393026062

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.