International Islamic University Malaysia (IIUM), Gombak, Malaysia.
Comput Biol Med. 2010 Jan;40(1):81-9. doi: 10.1016/j.compbiomed.2009.11.004. Epub 2009 Dec 22.
The use of vascular intersection aberration as one of the signs when monitoring and diagnosing diabetic retinopathy from retina fundus images (FIs) has been widely reported in the literature. In this paper, a new hybrid approach called the combined cross-point number (CCN) method able to detect the vascular bifurcation and intersection points in FIs is proposed. The CCN method makes use of two vascular intersection detection techniques, namely the modified cross-point number (MCN) method and the simple cross-point number (SCN) method. Our proposed approach was tested on images obtained from two different and publicly available fundus image databases. The results show a very high precision, accuracy, sensitivity and low false rate in detecting both bifurcation and crossover points compared with both the MCN and the SCN methods.
血管交叉偏差的使用作为从视网膜眼底图像 (FIs) 监测和诊断糖尿病性视网膜病变的标志之一，在文献中已有广泛报道。在本文中，提出了一种称为组合交叉点数量 (CCN) 方法的新混合方法，该方法能够检测 FIs 中的血管分叉和交点。CCN 方法利用了两种血管交叉检测技术，即改进的交叉点数量 (MCN) 方法和简单的交叉点数量 (SCN) 方法。我们的方法在来自两个不同的公开眼底图像数据库的图像上进行了测试。与 MCN 和 SCN 方法相比，该方法在检测分叉点和交叉点方面具有非常高的精度、准确性、灵敏度和低误报率。
