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ISSN      1003-9775
CN        11-2925/TP
邮发代号:82-456
单    价:80.00元
全年订价:960.00元
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基于置信度计算的快速眼底图像视盘定位

吴 慧1,2), 陈再良1,2), 欧阳平波1,3), 陈昌龙1,2), 邹北骥1,2)*
1) (中南大学信息科学与工程学院 长沙 410083)2) (有色金属工业信息化与自动化工程技术研究中心 长沙 410083)3) (中南大学湘雅二医院眼科 长沙 410083)
分类号: TP391.41
出版年,卷(期):页码: 2017 , 29 ( 6 ): 984-991 吴慧
摘要: 眼底图像视盘定位是视盘分割的重要前提. 针对视盘定位结果易受图像对比度的影响的问题, 提出一种基于置信度计算的快速视盘定位方法. 首先采用基于形态学变换的方法增强眼底图像中视盘、血管区域与图像背景的对比度, 并根据图像增强结果中像素点的亮度特征初始定位视盘区域; 然后运用局部滑动窗口扫描的方法, 根据窗口内像素点亮度特征和其周围血管分布的特性计算候选区域的置信度, 定位视盘区域. 在不同的眼底图像公共数据上进行实验的结果表明, 对于1 341幅眼底图像, 该方法能准确地定位其中1 325幅图像的视盘区域, 视盘定位准确率为98.8%, 平均每幅图像耗时0.25 s, 优于现有的视盘定位方法, 适用于眼底疾病的计算机辅助诊断.
关键词: 眼底图像; 视盘定位; 形态学变换; 滑动窗口扫描; 计算机辅助诊断
Fast Optic Disk Localization Based on Confidence Score Computation
Wu Hui1,2), Chen Zailiang1,2), Ouyang Pingbo1,3), Chen Changlong1,2), and Zou Beiji1,2)*
1) (School of Information Science and Engineering, Central South University, Changsha 410083) 2) (Center for Information and Automation of China Nonferrous Metals Industry Association, Changsha 410083)3) (Ophthalmology Department of the Second Xiangya Hospital, Central South University, Changsha 410083)
abstract: The optic disk localization is an important step before disk segmentation of fundus images. Since the optic disk localization can be easily influenced by the image contrast, we propose a fast optic disk localization method based on confidence score computation. Firstly, we perform morphological transformations to enhance the contrast between the optic disk and vessel regions from the background. According to the intensity features of pixels in the enhanced image, we localize the disk region roughly. Then, we apply the local sliding window scanning method to roughly localize the disk region and compute the confidence score of each candidate region based on the pixel intensity features in the window and the neighborhood vessel properties to generate the optic disk localization result. We conducted experiments on several publicly available datasets. The results show that the proposed method can successfully localize 1 325 optic regions among 1 341 images, and achieves 98.8% accuracy of the optic disk localization with each image consuming 0.25 s on average. The proposed method outperforms other existing optic disk localization methods and can be used in computer-aided eye disease diagnosis.
keyword: fundus images; optic disk localization; morphological transformations; sliding window scanning;
 
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