November 2019 in “Journal of Vertebrate Biology” QIA-64 software can measure straight wire lengths accurately but needs improvement for curved wires and width measurements.
5 citations
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January 2025 in “BMC Medical Informatics and Decision Making” 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.
January 2017 in “British journal of dermatology/British journal of dermatology, Supplement” December 2021 in “Acta dermato-venereologica” This study developed a deep learning framework and quantitative model that accurately predict basic and specific classification in male androgenetic alopecia by analyzing trichoscopic images.
April 2023 in “Journal of Investigative Dermatology” A new image-based method improves accuracy in measuring hair loss in mice.
This study describes a new method using ImageJ to quantitatively assess hair loss in mice with alopecia areata, offering a more precise and reproducible alternative to traditional visual scoring systems by employing image-based analysis techniques.
12 citations
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July 2016 in “British journal of dermatology/British journal of dermatology, Supplement” This study observed phenotypic diversity in hair loss among Japanese individuals homozygous for the LIPH c.736T>A mutation and suggests that differences in hair thickness may contribute to varying severities.
March 2026 in “Applied Sciences” In this scoping review, researchers observed that while AI-assisted trichoscopy holds promise for standardized assessments of hair and scalp disorders, its clinical translation is limited by small proprietary datasets, inconsistent validation protocols, and a scarcity of real-world clinical studies.
2 citations
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August 2006 in “Journal of Dermatological Science” Automated image analysis helps diagnose and monitor alopecia areata by efficiently measuring hair follicles.
3 citations
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January 1994 in “Journal of Society of Cosmetic Chemists of Japan” This study found that a hair tonic increased hair growth and reduced resting hair ratios in men with alopecia.
9 citations
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September 2022 in “Frontiers in Physics” This study found that Mueller Matrix microscopy can accurately identify, detect, and evaluate hair follicles in mouse skin tissue, suggesting its potential for skin structure research and dermatological applications.
10 citations
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January 2020 in “Royal Society Open Science” This study developed a quantitative measure for scoring hair surface damage from SEM images and found it accurately classified hair damage caused by explosive blasts, similar to an existing classification system.
2 citations
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July 2025 in “Drug development & registration” This study developed and tested a new algorithm for analyzing coat and skin coloration in laboratory animals, using digital images and hierarchical color clustering, which effectively quantified color proportions and tracked changes over time without specialized software.
December 2024 in “Tissue and Cell” In this study, researchers developed a method to automatically detect androgen receptor nuclear translocation in dermal papilla cells using fluorescence markers and image analysis, finding that the receptor's nuclear signal peaks about 20 minutes after DHT exposure.
This study used TikTok videos to explore experiences of individuals with lupus erythematosus, revealing that mucocutaneous symptoms significantly impact mental health and body image, while pharmacologic treatments are often viewed negatively, leading to important implications for clinical interactions and validation.
September 2017 in “Journal of Investigative Dermatology” Certain products and treatments can improve hair health and growth.
February 2008 in “Basic and clinical dermatology” Photographic imaging is crucial for documenting and managing hair loss, requiring careful preparation and standardization to be effective.
56 citations
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September 2013 in “Experimental Dermatology” This guide reviews the biology of sebaceous glands and their evaluation methods, emphasizing their roles beyond lipid production in skin health and disease, and reports no new research results.
1 citations
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September 2017 in “Journal of Investigative Dermatology” This study reported that introducing the TERT and Bmi1 genes into mouse dermal papilla cells resulted in immortal cells capable of inducing new hair follicles in vivo, and human immortal DPCs were also developed.
2 citations
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January 2024 in “Journal of Emerging Investigators” In this study, researchers evaluated deep learning methods for diagnosing Alopecia Areata and found that a modified Inception-Resnet-v2 model achieved a high validation accuracy of 97.94% and loss of 10.4%, suggesting it as an effective tool for classifying alopecia-affected hair.
1 citations
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March 2015 in “Journal of Visualized Experiments” This study developed a method to quantify hair loss in mice, aiding the evaluation of new treatments for alopecia.
7 citations
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September 2014 in “European Journal of Dermatology” This study found a significant positive correlation between hair thickness and growth rate, with a notably slower growth rate observed in men with male pattern hair loss compared to healthy controls.
April 2024 in “JMIR infodemiology” This study found that TikTok provides valuable insights into experiences with lupus erythematosus, highlighting distress from symptoms, negative perceptions of pharmacologic treatments, and issues with feeling "medically gaslighted.
This study developed an automated image analysis framework for diagnosing hair disorders using trichoscopic images, reporting a Random Forest classifier as having an 86.67% accuracy in distinguishing between different scalp pathologies based on quantitative image features.
September 2017 in “Journal of Investigative Dermatology” This study found that after four weeks of daily use, the roughness of the hair surface significantly decreased, as shown through quantitative image analysis using HIROX.
August 2023 in “Institutional Repositories DataBase (IRDB)” This research explored the impact of anticancer drugs on the scalp and found significant differences in scalp texture and features associated with alopecia, suggesting potential for assessing scalp morphology and changes during the hair regrowth process through image analysis.
January 2023 in “MIMESIS” This study interpreted McDonald's Father's Day advertising posters using semiotic analysis, finding that the imagery and text symbolically represent a father figure and McDonald's branding to celebrate the occasion.
January 2018 in “Surgical and Cosmetic Dermatology” In this study, researchers validated a software-based method that quantitatively assesses the effectiveness of treatments for hair loss by calculating the area of hair loss using contrast in standardized photographs, proving effective for both early and advanced cases of androgenetic alopecia and telogen effluvium.
32 citations
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March 2016 in “American Journal of Physical Anthropology” This study suggests that chemical methods can reveal subtle differences in scalp hair color variability across populations and emphasizes the need for enhanced understanding of hair fiber curvature.
January 2014 in “Anales Médicos de la Asociación Médica del Centro Médico ABC” This study suggests that a combination of topical minoxidil with oral finasteride and dutasteride may promote new hair growth in androgenetic alopecia, with minor safety concerns reported.