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
Hyperspectral imaging-based erythema classification in atopic dermatitis.
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. It has been retracted, and should not be counted. Cited by 8 papers.
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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.
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Who cites it
8 citing papers in PubMed, 12 citations in OpenAlex.
- Differentiating solar lentigines from post-inflammatory hyperpigmentation with hyperspectral imaging: A pilot study.International journal of cosmetic science · 2026Article
- Assessment of cold atmospheric pressure plasma therapy initiated at peak severity in a mouse model of radiation dermatitis.Scientific reports · 2026Article
- Hyperspectral image wavelength band and texture characteristics related to elasticity values for each body part for non-invasive skin elasticity analysis.Biomedical optics express · 2025Article
- Skin Lesion Classification in Head and Neck Cancers Using Tissue Index Images Derived from Hyperspectral Imaging.Cancers · 2025Article
- Advancing hyperspectral imaging and machine learning tools toward clinical adoption in tissue diagnostics: A comprehensive review.APL bioengineering · 2024Review
- A pilot study of skin barrier function in patients with systemic sclerosis and primary Sjögren's syndrome.Journal of rheumatic diseases · 2024Article
- 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) · 2024Article
- Hyperspectral imaging-based erythema classification in atopic dermatitis.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) · 2024Article
Corrections and comments
- Retraction · 2025-10-21Compromised Peer Review · Concerns/Issues about Methods · Concerns/Issues about Results and/or Conclusions · Investigation by Journal/Publisher · Results Not Reproducible ·
- Retracted
Authors and funding
2 authors at 1 institution in 2 countries.
Funding
Abstract
background/purposeAmong the characteristics that appear in the epidermis of the skin, erythema is primarily evaluated through qualitative scales, such as visual assessment (VA). However, VA is not ideal because it relies on the experience and skill of dermatologists. In this study, we propose a new evaluation method based on hyperspectral imaging (HSI) to improve the accuracy of erythema diagnosis in clinical settings and investigate the applicability of HSI to skin evaluation.
methodsFor this study, 23 subjects diagnosed with atopic dermatitis were recruited. The inside of the right arm is selected as the target area and photographed using a hyperspectral camera (HS). Subsequently, based on the erythema severity visually assessed by a dermatologist, the severity classification performance of the RGB and HS images is compared.
resultsErythema severity is classified as high when using (i) all reflectances of the entire HSI band and (ii) a combination of color features (R of RGB, a* of CIEL*a*b*) and five selected bands through band selection. However, as the number of features increases, the amount of calculation increases and becomes inefficient; therefore, (ii), which uses only seven features, is considered to perform classification more efficiently than (i), which uses 150 features.
conclusionIn conclusion, we demonstrate that HSI can be applied to erythema severity classification, which can further increase the accuracy and reliability of diagnosis when combined with other features observed in erythema. Additionally, the scope of its application can be expanded to various studies related to skin pigmentation.
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Registered trials
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.