Reflectance Confocal Microscopy (RCM) is a non-invasive imaging technique
used in biomedical research and clinical dermatology. It provides virtual
high-resolution images of the skin and superficial tissues, reducing the need
for physical biopsies. RCM employs a laser light source to illuminate the
tissue, capturing the reflected light to generate detailed images of
microscopic structures at various depths. Recent studies explored AI and
machine learning, particularly CNNs, for analyzing RCM images. Our study
proposes a segmentation strategy based on textural features to identify
clinically significant regions, empowering dermatologists in effective image
interpretation and boosting diagnostic confidence. This approach promises to
advance dermatological diagnosis and treatment.

反射共聚焦显微镜（RCM）是一种非侵入性成像技术，用于生物医学研究和临床皮肤学。它提供了皮肤和表浅组织的虚拟高分辨率图像，减少了对物理活检的需求。RCM 采用激光光源照射组织，捕捉反射光生成不同深度微观结构的详细图像。最近的研究探索了 AI 和机器学习，特别是 CNN，用于分析 RCM 图像。本研究提出了一种基于纹理特征的分割策略，用于识别具有临床意义的区域，提升皮肤科医生的图像解释能力和诊断信心。这种方法有望推动皮肤病的诊断和治疗。