As changes in hard or soft oral tissues normally have a microbiological component, it is important to develop diagnostic techniques that support clinical evaluation, without destroying microbiological formation. The optical coherence tomography (OCT) represents an alternative to analyze tissues and microorganisms without the need for processing. This imaging technique could be defined as a fast, real-time, in situ, and non-destructive method. Thus, this study proposed the use of the OCT to visualize biofilm by Candida albicans in reline resins for removable prostheses. Three reline resins (Silagum-Comfort, Coe-Comfort, and Soft-Confort), with distinct characteristics related to water sorption and fungal inhibition were used. A total of 30 samples (10 for each resin group) were subjected to OCT scanning before and 96 h after inoculation with Candida albicans (URM 6547). The biofilm analysis was carried out through a 2D optical Callisto SD-OCT (930 nm) operated in the spectral domain. Then, the images were preprocessed using a 3×3 Gaussian filter to remove the noise, and then Otsu binarization, allowing segmentation and pixel counting. The layer’s biofilm formed was clearly defined and, indeed, its visualization is modified by water sorption of each material. Silagum-Comfort and Soft-Confort showed some similarities in the scattering of light between the clean and inoculated samples, in which, the latter samples presented higher values of light signal intensity. Coe-Comfort samples were the only ones that showed no differences between the clean or inoculated images. Therefore, the results of this study suggest that OCT is a viable technique to visualize the biofilm in reline materials. Because findings in the literature are still scarcely using the OCT technique to visualize biofilm in reline resins, further studies are encouraged. It should not contain any references or displayed equations.

为了评估眼科光学相干断层成像（OCT）设备的分辨率、视场角、图像匹配度、深度测量准确性等多个关键参数，确保设备输出量值的准确性与有效性，设计并研制了一种模拟真实人眼结构且参数可溯源的模拟眼，包含角膜和晶状体等人眼主要屈光结构。设计并依托3D打印技术加工了用于横向与轴向分辨率检测的三维分辨率板；设计加工了用于视场角检测的阶梯状同心圆环结构；同时设计加工了用于图像匹配度检测的交叉光纤组件和用于深度测量准确性参数检测的平行玻璃板组件，可适配于模拟眼眼底凹槽内。使用共焦拉曼显微镜对三维分辨率板尺寸溯源，横向和轴向最小可检测分辨率分别为9.7 μm和5.7 μm；使用尼康投影仪对同心圆环尺寸及光纤直径溯源，最大可检测视场角109.03°以及最小62.5 μm的图像匹配度检测；使用尼康高度计对平行玻璃板中心厚度溯源，其测量不确定度小于5 μm。经过对商用眼科OCT设备测试表明，结合微纳3D打印技术的计量校准用模拟眼具有精度高、集成度高、适用范围广、稳定性强等优点，适用于眼科OCT设备的计量校准。

Age-related Macular Degeneration (AMD) and Diabetic Macular Edema (DME) are two common retinal diseases for elder people that may ultimately cause irreversible blindness. Timely and accurate diagnosis is essential for the treatment of these diseases. In recent years, computer-aided diagnosis (CAD) has been deeply investigated and effectively used for rapid and early diagnosis. In this paper, we proposed a method of CAD using vision transformer to analyze optical coherence tomography (OCT) images and to automatically discriminate AMD, DME, and normal eyes. A classification accuracy of 99.69% was achieved. After the model pruning, the recognition time reached 0.010 s and the classification accuracy did not drop. Compared with the Convolutional Neural Network (CNN) image classification models (VGG16, Resnet50, Densenet121, and E±cientNet), vision transformer after pruning exhibited better recognition ability. Results show that vision transformer is an improved alternative to diagnose retinal diseases more accurately.

对谱域光学相干层析系统(SD-OCT)采用色散补偿方法进行优化，是提高系统成像质量的重要方式。本文提出了一种基于数值多项式拟合的色散补偿方法。该方法通过提取干涉信号的相位并解包裹，利用数值多项式对解包裹后的相位进行拟合，然后根据拟合出的高阶色散因子对干涉信号做相位补偿。本文利用SD-OCT系统测量出不同光程差位置处的轴向分辨率和信噪比，通过比较分析色散补偿前后系统的轴向分辨率及信噪比，来验证该方法的有效性和可靠性。结果表明，本文设计的色散补偿技术可以使系统具有良好的轴向分辨率，三阶多项式拟合相位的色散补偿方法在约1.5 mm的成像深度范围内有明显的优化效果。

It is necessary to investigate the wavelength-dependent variation rules of the refractive index of edible oils so as to explore the specificity of the dispersion in light propagation, imaging, and interference processes among different types of edible oil products. In this study, by deriving the refractive index equations of the double glass sheet holding device and oil, the reflectance spectra of three different types of oil samples, namely, peanut oil, colza oil, and kitchen waste oil, were measured via a spectrometer. Furthermore, the refractive index model of these different types of oil samples was investigated. Additionally, based on the oil dispersion characteristics, the dispersion of oil in optical coherence tomography (OCT) was compensated via deconvolution. In the wavelength range of λ∈ (380, 1500) nm, the analytical expressions of the double glass sheet holding device and oils are featured by practical reliability. The refractive indexes of three different types of oils n ∈ (1.38, 1.52) show normal dispersion characteristics. The Cauchy coeffi cient matrix of the oil refractive index can be used for oil identification; in particular, the healthy oil and waste oil differ significantly in terms of the Cauchy coefficient matrix in the infrared band. Oil dispersion has almost no influence on the phase spectra of oils but can enhance their amplitude spectra. The dispersion mismatch can be eliminated by calculating the convolution kernel. The envelope broadening factors of OCT interference signals of oil products are 0.84, 0.64, and 0.91, respectively. According to the present research results, the refractive index model of oil can effectively remove the influence of the holding device. The refractive indexes of three different types of oil samples show similar wavelength-dependent variation characteristics, which confirms the existence of many correlated components in these oil samples. The established refractive index model of oil in a wide spectral range, from the ultraviolet to the infrared band, can be adequately employed for identifying different types of oils. The numerical dispersion compensation based on the established refractive index model can enhance the axial resolution in OCT imaging.

In this study, we proposed a method to measure the epidermal thickness (ET) of skin based on deep convolutional neural network, which was used to determine the boundaries of skin surface and the ridge portion in dermal–epidermis junction (DEJ) in cross-section optical coherence tomography (OCT) images of fingertip skin. The ET was calculated based on the row difference between the surface and the ridge top, which is determined by search the local maxima of boundary of the ridge portion. The results demonstrated that the region of ridge portion in DEJ was well determined and the ET measurement in this work can reduce the effect of the papillae valley in DEJ by 9.85%. It can be used for quantitative characterization of skin to differentiate the skin diseases.