Automatic fundus image classification for computer-aided diagonsis

Shijian Lu*, Jiang Liu, Joo Hwee Lim, Zhuo Zhang, Tan Ngan Meng, Wing Kee Wong, Huiqi Li, Tian Yin Wong

*此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

5 引用 (Scopus)

摘要

With the advances of computer technology, more and more computer-aided diagnosis (CAD) systems have been developed to provide the "second opinion". This paper reports an automatic fundus image classification technique that is designed to screen out the severely degraded fundus images that cannot be processed by traditional CAD systems. The proposed technique classifies fundus images based on the image range property. In particular, it first calculates a number of range images from a fundus image at different resolutions. A feature vector is then constructed based on the histogram of the calculated range images. Finally, fundus images can be classified by a linear discriminant classifier that is built by learning from a large number of normal and abnormal training fundus images. Experiments over 644 fundus images of different qualities show that the classification accuracy of the proposed technique reaches above 96%.

源语言英语
主期刊名Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society
主期刊副标题Engineering the Future of Biomedicine, EMBC 2009
出版商IEEE Computer Society
1453-1456
页数4
ISBN(印刷版)9781424432967
DOI
出版状态已出版 - 2009
已对外发布
活动31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009 - Minneapolis, MN, 美国
期限: 2 9月 20096 9月 2009

出版系列

姓名Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009

会议

会议31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009
国家/地区美国
Minneapolis, MN
时期2/09/096/09/09

指纹

探究 'Automatic fundus image classification for computer-aided diagonsis' 的科研主题。它们共同构成独一无二的指纹。

引用此