Miyazawa Arata, Yamanari Masahiro, Makita Shuichi, Miura Masahiro, Kawana Keisuke, Iwaya Keiichi, Goto Hiroshi, Yasuno Yoshiaki
Computational Optics Group in University of Tsukuba, Ibaraki, Japan.
Opt Express. 2009 Sep 28;17(20):17426-40. doi: 10.1364/OE.17.017426.
We developed a tissue discrimination algorithm of polarization sensitive optical coherence tomography (PS-OCT) based on the optical properties of tissues. We calculated the three-dimensional (3D) feature vector from the parameters intensity, extinction coefficient, birefringence, which were obtained by PS-OCT. The tissue type of each pixel was determined according to the position of the feature vector in the 3D feature space. The algorithm was applied for discriminating tissues of the human anterior eye segment. The conjunctiva, sclera, trabecular meshwork (TM), cornea, and uvea were well separated in the 3D feature space, and we observed them with good contrast. The TM line can be observed in the 3D discriminated volume, as observed by gonioscopy.We validated our method by applying our algorithm and histological data to porcine eyes. A marker was injected into sub-Tenon's space and the tissues that were anterior to the marker and posterior to the marker were successfully segmented by our algorithm.
我们基于组织的光学特性开发了一种偏振敏感光学相干断层扫描（PS-OCT）的组织辨别算法。我们从通过PS-OCT获得的强度、消光系数、双折射等参数计算三维（3D）特征向量。根据特征向量在3D特征空间中的位置确定每个像素的组织类型。该算法用于辨别人类眼前节的组织。在3D特征空间中，结膜、巩膜、小梁网（TM）、角膜和葡萄膜被很好地分离，并且我们观察到它们具有良好的对比度。如通过前房角镜观察到的那样，在3D辨别体积中可以观察到TM线。我们通过将我们的算法和组织学数据应用于猪眼来验证我们的方法。将一个标记物注入Tenon囊下间隙，并且我们的算法成功地分割了标记物前方和后方的组织。
