Zheng Jian, Tian Jie, Dai Yakang, Deng Kexin, Chen Jian
Medical Image Processing Group, Key Laboratory of Complex Systems and Intelligence Science, Institute of Automation Chinese Academy of Sciences.
Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:102-5. doi: 10.1109/IEMBS.2009.5334778.
Retinal image registration is essential and crucial for ophthalmologists to diagnose various diseases. A great number of methods have been developed to solve this problem, however, fast and accurate retinal image registration is still a challenging problem since the great content complexity and low image quality of the unhealthy retina. This paper provides a new retinal image registration method based on salient feature regions (SFR). We first extract the SFR in each image based on a well defined region saliency metric. Next, SFR are matched by using an innovative local feature descriptor. Then we register those matched SFR using local rigid transformation. Finally, we register the two images adopting global second order polynomial transformation with locally rigid registered region centers as control points. Experimental results prove that our method is very fast and accurate, especially quite effective for the low quality retinal images registration.
视网膜图像配准对于眼科医生诊断各种疾病至关重要。为解决此问题已开发出大量方法，然而，由于不健康视网膜的内容复杂度高且图像质量低，快速准确的视网膜图像配准仍然是一个具有挑战性的问题。本文提出了一种基于显著特征区域（SFR）的新型视网膜图像配准方法。我们首先基于定义明确的区域显著性度量在每个图像中提取SFR。接下来，使用创新的局部特征描述符对SFR进行匹配。然后我们使用局部刚体变换对那些匹配的SFR进行配准。最后，我们以局部刚体配准区域中心作为控制点，采用全局二阶多项式变换对两幅图像进行配准。实验结果证明，我们的方法非常快速且准确，尤其对于低质量视网膜图像配准非常有效。
