Alonso-Caneiro David, Iskander D Robert, Collins Michael J
Contact Lens and Visual Optics Laboratory, School of Optometry, Queensland University of Technology, Brisbane, Qld. Q4059, Australia.
IEEE Trans Biomed Eng. 2009 May;56(5):1473-81. doi: 10.1109/TBME.2008.2011993. Epub 2009 Jan 23.
A new method for noninvasive assessment of tear film surface quality (TFSQ) is proposed. The method is based on high-speed videokeratoscopy in which the corneal area for the analysis is dynamically estimated in a manner that removes videokeratoscopy interference from the shadows of eyelashes but not that related to the poor quality of the precorneal tear film that is of interest. The separation between the two types of seemingly similar videokeratoscopy interference is achieved by region-based classification in which the overall noise is first separated from the useful signal (unaltered videokeratoscopy pattern), followed by a dedicated interference classification algorithm that distinguishes between the two considered interferences. The proposed technique provides a much wider corneal area for the analysis of TFSQ than the previously reported techniques. A preliminary study with the proposed technique, carried out for a range of anterior eye conditions, showed an effective behavior in terms of noise to signal separation, interference classification, as well as consistent TFSQ results. Subsequently, the method proved to be able to not only discriminate between the bare eye and the lens on eye conditions but also to have the potential to discriminate between the two types of contact lenses.
提出了一种用于无创评估泪膜表面质量（TFSQ）的新方法。该方法基于高速角膜地形图，其中分析的角膜区域通过一种动态估计的方式来确定，这种方式可以消除睫毛阴影对角膜地形图的干扰，但不会消除与感兴趣的角膜前泪膜质量差相关的干扰。通过基于区域的分类实现了两种看似相似的角膜地形图干扰之间的分离，首先将总体噪声与有用信号（未改变的角膜地形图模式）分离，然后是一种专门的干扰分类算法，用于区分两种所考虑的干扰。与先前报道的技术相比，所提出的技术为TFSQ分析提供了更宽的角膜区域。对一系列眼前部情况使用所提出的技术进行的初步研究表明，在噪声与信号分离、干扰分类以及TFSQ结果一致性方面具有有效表现。随后，该方法不仅被证明能够在眼部情况中区分裸眼和戴镜情况，而且有潜力区分两种类型的隐形眼镜。
