ArticleJournal of clinical medicine2020
Non-Invasive Skin Cancer Diagnosis Using Hyperspectral Imaging for In-Situ Clinical Support.
Article in Journal of clinical medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers, 2 of them syntheses that pooled it.
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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.
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Who cites it
42 citing papers in PubMed, 2 syntheses or guidelines pooled it, 109 citations in OpenAlex.
- Medical hyperspectral imaging: an updated review of technology advancements and biomedical applications.Journal of biomedical optics · 2026Pooled it
- Hyperspectral and multispectral image processing for gross-level tumor detection in skin lesions: a systematic review.Journal of biomedical optics · 2022Pooled it
- Emerging non-invasive tools for hair follicle assessment: a narrative review on hyperspectral and terahertz imaging.Lasers in medical science · 2026Review
- Novel Snapshot-Based Hyperspectral Conversion for Dermatological Lesion Detection via YOLO Object Detection Models.Bioengineering (Basel, Switzerland) · 2025Article
- Skin Lesion Classification in Head and Neck Cancers Using Tissue Index Images Derived from Hyperspectral Imaging.Cancers · 2025Article
- Article
- Detection of flap malperfusion after microsurgical tissue reconstruction using hyperspectral imaging and machine learning.Scientific reports · 2025Article
- Advancing hyperspectral imaging and machine learning tools toward clinical adoption in tissue diagnostics: A comprehensive review.APL bioengineering · 2024Review
- Article
- Article
- Systematic Meta-Analysis of Computer-Aided Detection of Breast Cancer Using Hyperspectral Imaging.Bioengineering (Basel, Switzerland) · 2024Review
- Advancements in Hyperspectral Imaging and Computer-Aided Diagnostic Methods for the Enhanced Detection and Diagnosis of Head and Neck Cancer.Biomedicines · 2024Review
- Classification of melanocytic lesions using direct illumination multispectral imaging.Scientific reports · 2024Article
- Pixel-level classification of pigmented skin cancer lesions using multispectral autofluorescence lifetime dermoscopy imaging.Biomedical optics express · 2024Article
- Acne Detection Based on Reconstructed Hyperspectral Images.Journal of imaging · 2024Article
- Facilitating clinically relevant skin tumor diagnostics with spectroscopy-driven machine learning.iScience · 2024Article
- Review of the application of the most current sophisticated image processing methods for the skin cancer diagnostics purposes.Archives of dermatological research · 2024Review
- 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
- Acceleration of Hyperspectral Skin Cancer Image Classification through Parallel Machine-Learning Methods.Sensors (Basel, Switzerland) · 2024Article
- Near-infrared hyperspectral imaging and robust statistics for in vivo non-melanoma skin cancer and actinic keratosis characterisation.PloS one · 2024Article
Corrections and comments
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Authors and funding
13 authors at 3 institutions in 1 country.
Funding
Abstract
Skin cancer is one of the most common forms of cancer worldwide and its early detection its key to achieve an effective treatment of the lesion. Commonly, skin cancer diagnosis is based on dermatologist expertise and pathological assessment of biopsies. Although there are diagnosis aid systems based on morphological processing algorithms using conventional imaging, currently, these systems have reached their limit and are not able to outperform dermatologists. In this sense, hyperspectral (HS) imaging (HSI) arises as a new non-invasive technology able to facilitate the detection and classification of pigmented skin lesions (PSLs), employing the spectral properties of the captured sample within and beyond the human eye capabilities. This paper presents a research carried out to develop a dermatological acquisition system based on HSI, employing 125 spectral bands captured between 450 and 950 nm. A database composed of 76 HS PSL images from 61 patients was obtained and labeled and classified into benign and malignant classes. A processing framework is proposed for the automatic identification and classification of the PSL based on a combination of unsupervised and supervised algorithms. Sensitivity and specificity results of 87.5% and 100%, respectively, were obtained in the discrimination of malignant and benign PSLs. This preliminary study demonstrates, as a proof-of-concept, the potential of HSI technology to assist dermatologists in the discrimination of benign and malignant PSLs during clinical routine practice using a real-time and non-invasive hand-held device.
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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.