基于眼底图像层次特征的分类方法

针对眼底图像中视网膜血管结构的划分问题，提出一种自适应的广度优先搜索算法。首先，基于视网膜血管的结构提出层次特征的概念并进行特征提取；然后，对分割的视网膜血管进行分析及处理，提取得到多个无向图子图；最后，使用自适应的广度优先搜索算法对每个子图中的层次特征进行分类。视网膜血管结构的划分问题被转化为层次特征的分类问题，通过对视网膜血管中的层次特征进行分类，包含这些层次特征的视网膜血管段的层次结构就可以被确定，从而实现视网膜血管结构的划分。该算法运用于公开的眼底图像数据库时具有良好的性能。

Classification Method Based on Hierarchical Features of Fundus Images

To solve the problem of retinal vascular structure division in fundus images, an adaptive breadth-first search algorithm was proposed. Firstly, based on the structure of retinal vessels, the concept of hierarchical features was proposed and feature extraction was carried out. Then, the segmented retinal vessels were analyzed and processed, and several undirected subgraphs were extracted. Finally, the adaptive breadth-first search algorithm was used to classify the hierarchical features in each subgraph. The division of retinal vascular structure was transformed into the classification of hierarchical features. By classifying the hierarchical features of retinal vessels, the hierarchical structures of retinal vascular segments containing these hierarchical features were able to be determined, thus realizing the division of retinal vascular structures. The algorithm has excellent performance when applied to public fundus image databases.