Treffer: Automatic measurement of skin textures of the dorsal hand in evaluating skin aging.

Title:
Automatic measurement of skin textures of the dorsal hand in evaluating skin aging.
Source:
Skin Research & Technology; May2013, Vol. 19 Issue 2, p145-151, 7p, 2 Black and White Photographs, 3 Charts, 3 Graphs
Reviews & Products:
Database:
Complementary Index

Weitere Informationen

Background/purpose Changes in skin textures have been used to evaluate skin aging in many studies. In our previous study, we built some skin texture parameters, which can be used to evaluate skin aging of human dorsal hand. However, it will take too much time and need to work arduously to get the information from digital skin image by manual work. So, we want to build a simple and effective method to automatically count some of those skin texture parameters by using digital image-processing technology. Methods A total of 100 subjects aged 30 years and above were involved. Sun exposure history and demographic information were collected by using a questionnaire. The skin image of subjects' dorsal hand was obtained by using a portable skin detector. The number of grids, which is one of skin texture parameters built in our previous study, was measured manually and automatically. Automated image analysis program was developed by using Matlab 7.1 software. Results The number of grids counted automatically ( NGA) was significantly correlated with the number of grids counted manually ( NGM) ( r = 0.9287, P < 0.0001). And in each age group, there were no significant differences between NGA and NGM. The NGA was negatively correlated with age and lifetime sun exposure, and decreased with increasing Beagley-Gibson score from 3 to 6. In addition, even after adjusting for NGA, the standard deviation of grid areas for each image was positively correlated with age, sun exposure, and Bealey-Gibson score. Conclusion The method introduced in present study can be used to measure some skin aging parameters automatically and objectively. And it will save much time, reduce labor, and avoid measurement errors of deferent investigators when evaluating a great deal of skin images in a short time. [ABSTRACT FROM AUTHOR]

Copyright of Skin Research & Technology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)