Skin Image Analysis for Detection and Quantitative Assessment of Dermatitis, Vitiligo, and Alopecia Areata Lesions: A Systematic Literature Review

    January 2025 in “ BMC Medical Informatics and Decision Making ”
    Athanasios Kallipolitis, Κωνσταντίνος Μούτσελος, Argyriοs Zafeiriou … Ilias Maglogiannis
    Studysummary This review examines the use of computer vision techniques, specifically deep learning architectures and image processing algorithms, for detecting and assessing skin conditions like vitiligo and dermatitis, and highlights the need for disease-specific datasets to improve automated diagnostic tools in dermatology.
    Automatically generated from the study's abstract, not written by a person, and not a review of the full paper. Not medical advice or a treatment recommendation. Read the original study, and consult a qualified healthcare professional before changing treatment. Full disclaimer
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    Research cited in this study 15

    1. Multi-Class Support Vector Machine Classification for Detecting Alopecia Areata and Scalp Diseases International Journal on Recent and Innovation Trends in Computing and Communication · 2023
    2. Ensemble of Pre-Learned Deep Learning Model and an Optimized LSTM for Alopecia Areata Classification Journal of Intelligent & Fuzzy Systems · 2023
    3. Two-Dimensional Planimetry for Alopecia Areata Severity Evaluation Compared With Severity of Alopecia Tool: A Pilot Study Skin Research and Technology · 2023
    4. AB-MTE Deep Classifier Trained with AAGAN for the Identification and Classification of Alopecia Areata Engineering Technology & Applied Science Research · 2023
    5. Attention Balanced Multi-Dimension Multi-Task Deep Learning for Alopecia Recognition Indian journal of science and technology · 2023
    6. Prediction of Alopecia Areata Using CNN 2023
    7. Alopecia Areata: An Updated Review for 2023 Journal of Cutaneous Medicine and Surgery · 2023
    8. FRCNN Based Deep Learning for Identification and Classification of Alopecia Areata 2023
    9. Automating Hair Loss Labels for Universally Scoring Alopecia from Images JAMA Dermatology · 2022
    10. An Analysis of Alopecia Areata Classification Framework for Human Hair Loss Based on VGG-SVM Approach Journal of Pharmaceutical Negative Results · 2022
    11. Alopecia Areata: An Update on Etiopathogenesis, Diagnosis, and Management Clinical Reviews in Allergy & Immunology · 2021
    12. Classification Framework for Healthy Hair and Alopecia Areata: A Machine Learning Approach Computational and Mathematical Methods in Medicine · 2021
    13. Pre-Trained Classification of Scalp Conditions Using Image Processing Indonesian Journal of Electrical Engineering and Computer Science · 2020
    14. Quantifying Alopecia Areata via Texture Analysis to Automate the SALT Score Computation Journal of Investigative Dermatology Symposium Proceedings · 2017
    15. Investigative Guidelines for Alopecia Areata Dermatologic therapy · 2011

    Related research 1

    1. Serum Zinc Concentration in Patients With Alopecia Areata Acta dermato-venereologica (Print) · 2023