Optical coherence tomography (OCT) provides a non-invasive method for in-vivo imaging of sub-surface skin tissue. Many skin features such as sweat glands and blisters are clearly observable in OCT images. It seems therefore probable that OCT could be used for the detection and identification of lesions and skin cancers. These applications, however, have not been well developed. One area in dermatology where OCT has been applied is the measurement of epidermal thickness. OCT images are inherently noisy and measurements based on them require intensive manual processing. A robust method to automatically detect and measure features of interest is necessary to enable routine application of OCT. As a first step, we approach the seemingly straightforward problem of measuring epidermal thickness. In this paper we describe a novel shapelet-based image processing technique for the automatic identification of the upper and lower boundaries of the epidermis in living human skin tissue. These boundaries are used to measure epidermal thickness. To our knowledge, this is the first report of automated feature identification and measurement from OCT images of skin.
The use of Raman microscopy in imaging two emulsion systems is described. Registered optical microscopy and Raman images are collected, the latter describing the chemical basis of the heterogeneity observed in the former. These examples act as a powerful demonstration of the application of the Raman microscopy technique to the analysis and understanding of microstructure in commercial products. The results indicate how the principles of Raman imaging can be applied to complex, multicomponent, multiphase systems of inherently low contrast. Such systems are of importance because they represent a wide variety of commercial product systems, ranging from pharmaceutical creams through skin creams and toothpastes. The use of a software environment for the organization, storage, management, interrogation, and manipulation of multidimensional spectral imaging data is also described. The important factors to be considered in determining the full information content of such data sets are established, and suggestions as to how such data sets can be optimally interrogated are made.
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