Work

A quantitative evaluation method of laser treatment efficacy for pigmentary dermatosis based on image segmentation technology

Year: 2024
Type: article
Abstract: A growing number of skin laser treatments have rapidly evolved and increased their role in the field of dermatology, laser treatment is considered to be used for a variety of pigmentary dermatosis as well as aesthetic problems. The standardized assessment of laser treatment efficacy is crucial for the interpretation and comparison of studies related to laser treatment of skin disorders. In this study, we propose an evaluation method to quantitatively assess laser treatment efficacy based on the image segmentation technology. A tattoo model of Sprague Dawley (SD) rats was established and treated by picosecond laser treatments at varying energy levels. Images of the tattoo models were captured before and after laser treatment, and feature extraction was conducted to quantify the tattooed area and pigment gradation. Subsequently, the clearance rate, which has been a standardized parameter, was calculated. The results indicate that the clearance rates obtained through this quantitative algorithm are comparable and exhibit smaller standard deviations compared with scale scores (4.59% versus 7.93% in the low-energy group, 4.01% versus 9.05% in the medium-energy group, and 4.29% versus 10.23% in the high-energy group). This underscores the greater accuracy, objectivity, and reproducibility in assessing treatment responses. The quantitative evaluation of pigment removal holds promise for facilitating faster and more robust assessments in research and development. Additionally, it may enable the optimization of treatments tailored to individual patients, thereby contributing to more effective and personalized dermatological care.
Authors: Haopu Jian, Qi Chen, Youjun Yu, Cheng Wang, Peiru Wang, Xiuli Wang
Language: English
Subfield: Dermatology
Field: Medicine
Open Access status: gold
Estimated APC paid: $1,500
OpenAlex ID: W4403837805
FWCI:
Cites: 27
Cited by:
Related to: 10