A novel automated approach to rapid and precise in vivo measurement of hair morphometrics using a smartphone. Issue 6 (12th July 2021)

• Record Type: Journal Article
• Authors: Majd, Ali; AlJasser, Mohammed; Mirzaalian, Hengameh; Shapiro, Jerry; Hamarneh, Ghassan; Lui, Harvey; Santos, Leopoldo Duailibe Nogueira; Chu, Thomas; Lee, Tim K.
• Is Part Of: Skin research and technology. Volume 27:Issue 6(2021)
• Page Start: 1128
• Page End: 1134
• Publication Date: 2021-07-12
• Subjects: alopecia -- image processing -- scalp -- trichometry -- trichoscopy; Skin -- Research -- Periodicals; Skin -- Diseases -- Periodicals; Skin -- Physiology -- Periodicals; 616.5
• DOI: 10.1111/srt.13076
• Languages: English
• ISSNs: 0909-752X

Abstract

Abstract: Background: Although many hair disorders can be readily diagnosed based on their clinical appearance, their progression and response to treatment are often difficult to monitor, particularly in quantitative terms. We introduce an innovative technique utilizing a smartphone and computerized image analysis to expeditiously and automatically measure and compute hair density and diameter in patients in real time. Methods: A smartphone equipped with a dermatoscope lens wirelessly transmits trichoscopy images to a computer for image processing. A black‐and‐white binary mask image representing hair and skin is produced, and the hairs are thinned into single‐pixel‐thick fiber skeletons. Further analysis based on these fibers allows morphometric characteristics such as hair shaft number and diameters to be computed rapidly. The hair‐bearing scalps of fifty participants were imaged to assess the precision of our automated smartphone‐based device in comparison with a specialized trichometry device for hair shaft density and diameter measurement. The precision and operation time of our technique relative to manual trichometry, which is commonly used by hair disorder specialists, is determined. Results: An equivalence test, based on two 1‐sided t tests, demonstrates statistical equivalence in hair density and diameter values between this automated technique and manual trichometry within a 20% margin. On average, this technique actively required 24 seconds of the clinician's time whereas manual trichometry necessitated 9.2 minutes. Conclusion: Automated smartphone‐based trichometry is a rapid, precise, and clinically feasible technique which can significantly facilitate the assessment and monitoring of hair loss. Its use could be easily integrated into clinical practice to improve standard trichoscopy.