College of Computer Science, Shenyang Aerospace University, Shenyang, Liaoning, China.
School of Software, Jiangxi Normal University, Nanchang, Jiangxi, China.
Comput Math Methods Med. 2019 Nov 20;2019:8973287. doi: 10.1155/2019/8973287. eCollection 2019.
Accurate optic disc and optic cup segmentation plays an important role for diagnosing glaucoma. However, most existing segmentation approaches suffer from the following limitations. On the one hand, image devices or illumination variations always lead to intensity inhomogeneity in the fundus image. On the other hand, the spatial prior knowledge of optic disc and optic cup, e.g., the optic cup is always contained inside the optic disc region, is ignored. Therefore, the effectiveness of segmentation approaches is greatly reduced. Different from most previous approaches, we present a novel locally statistical active contour model with the structure prior (LSACM-SP) approach to jointly and robustly segment the optic disc and optic cup structures. First, some preprocessing techniques are used to automatically extract initial contour of object. Then, we introduce the locally statistical active contour model (LSACM) to optic disc and optic cup segmentation in the presence of intensity inhomogeneity. Finally, taking the specific morphology of optic disc and optic cup into consideration, a novel structure prior is proposed to guide the model to generate accurate segmentation results. Experimental results demonstrate the advantage and superiority of our approach on two publicly available databases, i.e., DRISHTI-GS and RIM-ONE r2, by comparing with some well-known algorithms.
准确的视盘和视杯分割对视神经疾病的诊断起着重要作用。然而，大多数现有的分割方法都存在以下局限性。一方面，图像设备或照明变化总会导致眼底图像的强度不均匀。另一方面，视盘和视杯的空间先验知识（例如，视杯总是包含在视盘区域内）被忽略了。因此，分割方法的有效性大大降低。与大多数先前的方法不同，我们提出了一种新的基于局部统计主动轮廓模型和结构先验的方法（LSACM-SP），用于联合且稳健地分割视盘和视杯结构。首先，采用一些预处理技术来自动提取目标的初始轮廓。然后，我们在存在强度不均匀的情况下引入局部统计主动轮廓模型（LSACM）进行视盘和视杯分割。最后，考虑到视盘和视杯的特定形态，提出了一种新的结构先验来指导模型生成准确的分割结果。实验结果表明，与一些知名算法相比，我们的方法在两个公开可用的数据库（即 DRISHTI-GS 和 RIM-ONE r2）上具有优势和优越性。
