K-F环自动检测系统设计

Design of automatic K-F ring measuring system

考虑Kayser-Fleischer(K-F)环自动检测系统可以用于威尔逊氏病(wilson's disease,WD)的辅助诊断,本文针对现有的威尔逊氏病检测方法均没有考虑光照及角膜老年环的影响,通过分析彩色图像中Kayser-Fleischer(K-F)环的分布特征,设计了K-F环自动检测系统。该系统通过对图像进行预处理获得目标检测候选区域,通过梯度响应最优算法精确检测K-F环的边界信息。为了降低光照对算法有效性影响,建立了光照检测模型来提高检测系统的鲁棒性。最后,定义宽度特征算子排除正常图像的影响,定义颜色特征算子排除角膜老年环的影响。实验分析显示,在采集的2 234幅图像中,本文提出的K-F环自动检测系统的识别率能够达到98.4%,而且系统不受角膜老年环的影响。

Automatic Kayser-Fleischer（K-F）ring measuring systems are able to help the diagnosis of the Wilson＇s disease.As traditional diagnosis methods for the Wilson＇s disease ignore the influence of illumination and the corneal arcus on the detection precision,this paper designs an automatic K-F ring measuring system according to the（K-F）ring distribution in a color image.With the system,the Region of Interest（ROI）of an iris image was extracted by pretreatment.Then,the boundary of K-F ring was detected by the integral optimization of gradient algorithm and boundary tracking algorithm.To reduce the influence of the illumination on the validity of the algorithm,an illumination detection model was established to improve the robustness of the measuring system.Finally,the width features and color features were defined to remove the effects by normal images and corneal arcus.2 234 iris images collected from our database were analyzed and the analyzed results indicate that the classification accuracy of the proposed K-F ring measuring system reaches 98.4%.It still has good performance if the patient has the corneal arcus.