Department of Software Convergence, Graduate School, Soonchunhyang University, Asan City, Chungnam, Republic of Korea.
Department of Medical IT Engineering, College of Medical Sciences, Soonchunhyang University, Asan City, Chungnam, Republic of Korea.
Skin Res Technol. 2024 Mar;30(3):e13654. doi: 10.1111/srt.13654.
BACKGROUND/PURPOSE: Skin elasticity was used to evaluate healthy and diseased skin. Correlation analysis between image texture characteristics and skin elasticity was performed to study the feasibility of assessing skin elasticity using a non-contact method.
Skin images in the near-infrared band were acquired using a hyperspectral camera, and skin elasticity was obtained using a skin elastimeter. Texture features of the mean, standard deviation, entropy, contrast, correlation, homogeneity, and energy were extracted from the acquired skin images, and a correlation analysis with skin elasticity was performed.
The texture features, and skin elasticity of skin images in the near-infrared band had the highest correlation on the side of eye and under of arm, and the mean and correlation were features of texture suitable for distinguishing skin elasticity according to the body part.
In this study, we performed elasticity and correlation analyses for various body parts using the texture characteristics of skin hyperspectral images in the near-infrared band, confirming a significant correlation in some body parts. It is expected that this will be used as a cornerstone of skin elasticity evaluation research using non-contact methods.
背景/目的:皮肤弹性用于评估健康和患病皮肤。对图像纹理特征与皮肤弹性之间的相关性进行分析,研究使用非接触方法评估皮肤弹性的可行性。
使用高光谱相机获取近红外波段的皮肤图像,并使用皮肤弹性计获取皮肤弹性。从获取的皮肤图像中提取均值、标准差、熵、对比度、相关性、同质性和能量等纹理特征,并与皮肤弹性进行相关性分析。
近红外波段皮肤图像的纹理特征和皮肤弹性在眼侧和手臂下侧相关性最高,根据身体部位,均值和相关性是适合区分皮肤弹性的纹理特征。
本研究使用近红外波段皮肤高光谱图像的纹理特征对不同身体部位进行弹性和相关性分析,确认了一些身体部位存在显著相关性。有望成为非接触式皮肤弹性评估研究的基石。