We explore the possibility of detecting anomalous structures buried under the skin surface by studying the deviations from the ideal Airy pattern of the point-spread function (PSF) of a terahertz microscope that includes the skin as one of the reflecting surfaces of the optical system. Using a custom terahertz microscope with a monochromatic point source emitting at 0.611 THz, we record the PSF images with a microbolometer camera. Skin simulants based on collagen gel, with and without artificial buried structures, have been analyzed. The geometrical features characterizing the PSF deformations have been extracted automatically from the PSF images. A machine learning algorithm applied to these geometrical features produces a reliable classification of targets with or without buried structures with error below 5%. It can even classify targets with anisotropic buried structures according to their different orientation.

我们通过研究太赫兹显微镜的点扩散函数 (PSF) 与理想艾里模式的偏差，探索检测隐藏在皮肤表面下的异常结构的可能性，该显微镜将皮肤作为光学系统的反射面之一。使用带有以 0.611 THz 发射的单色点源的定制太赫兹显微镜，我们用微测辐射热计相机记录 PSF 图像。已经分析了基于胶原凝胶的皮肤模拟物，包括和不包括人工埋藏结构。表征 PSF 变形的几何特征已从 PSF 图像中自动提取。应用于这些几何特征的机器学习算法可以对带有或不带有掩埋结构的目标进行可靠分类，误差低于 5%。