A framework for retinal vasculature segmentation based on matched filters.
BACKGROUND
Automatic fundus image processing plays a significant role in computer-assisted retinopathy diagnosis. As retinal vasculature is an important anatomical structure in ophthalmic images, recently, retinal vasculature segmentation has received considerable attention from researchers. A segmentation method usually consists of three steps: preprocessing, segmentation, post-processing. Most of the existing methods emphasize on the segmentation step. In our opinion, the vessels and background can be easily separable when suitable preprocessing exists.


METHODS
This paper represents a new matched filter-based vasculature segmentation method for 2-D retinal images. First of all, a raw segmentation is acquired by thresholding the images preprocessed using weighted improved circular gabor filter and multi-directional multi-scale second derivation of Gaussian. After that, the raw segmented image is fine-tuned by a set of novel elongating filters. Finally, we eliminate the speckle like regions and isolated pixels, most of which are non-vessel noises and miss-classified fovea or pathological regions.


RESULTS
The performance of the proposed method is examined on two popularly used benchmark databases: DRIVE and STARE. The accuracy values are 95.29 and 95.69 %, respectively, without a significant degradation of specificity and sensitivity.


CONCLUSIONS
The performance of the proposed method is significantly better than almost all unsupervised methods, in addition, comparable to most of the existing supervised vasculature segmentation methods.
School of Computer Science and Technology, Shandong University, 250101, Jinan, China. rongmengyuan@gmail.com.
Xianjing
X
Meng
School of Computer Science and Technology, Shandong University, 250101, Jinan, China. ylyin@sdu.edu.cn.|School of Computer Science and Technology, Shandong University of Finance and Economics, 250014, Jinan, China. ylyin@sdu.edu.cn.
Yilong
Y
Yin
School of Computer Science and Technology, Shandong University, 250101, Jinan, China. gpyang@sdu.edu.cn.
Gongping
G
Yang
School of Computer Science and Technology, Shandong University, 250101, Jinan, China. hanzhegzyx@163.com.
Zhe
Z
Han
School of Computer Science and Technology, Shandong University, 250101, Jinan, China. xwyan6@gmail.com.
Xiaowei
X
Yan
D000465:Algorithms; D019540:Area Under Curve; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D012372:ROC Curve; D015861:Retinal Neovascularization / Q000175:diagnosis*