Palmer Gregory M, Ramanujam Nirmala
Department of Radiation Oncology, Duke University, Durham, NC 27710, USA.
IEEE Trans Biomed Eng. 2007 Aug;54(8):1533-5. doi: 10.1109/TBME.2006.889779.
This paper outlines a framework by which the optimal illumination/collection geometry can be identified for a particular biomedical application. In this paper, this framework was used to identify the optimal probe geometry for the accurate determination of tissue optical properties representative of that in the ultraviolet-visible (UV-VIS) spectral range. An optimal probe geometry was identified which consisted of a single illumination and two collection fibers, one of which is insensitive to changes in scattering properties, and the other is insensitive to changes in the attenuation coefficient. Using this probe geometry in conjunction with a neural network algorithm, the optical properties could be extracted with root-mean-square errors of 0.30 cm(-1) for the reduced scattering coefficient (tested range of 3-40 cm(-1)), and 0.41 cm(-1) for the absorption coefficient (tested range of 0-80 cm(-1)).
本文概述了一个框架，通过该框架可以为特定的生物医学应用确定最佳的照明/采集几何结构。在本文中，该框架用于确定最佳探头几何结构，以准确测定代表紫外可见（UV-VIS）光谱范围内组织的光学特性。确定了一种最佳探头几何结构，它由一根照明光纤和两根采集光纤组成，其中一根对散射特性的变化不敏感，另一根对衰减系数的变化不敏感。将这种探头几何结构与神经网络算法结合使用，对于约化散射系数（测试范围为3-40 cm(-1)），可以以均方根误差0.30 cm(-1)提取光学特性；对于吸收系数（测试范围为0-80 cm(-1)），均方根误差为0.41 cm(-1)。
