首页> 外文会议>International Conference on Biomedical Engineering >ARGALI: An Automatic Cup-to-Disc Ratio Measurement System for Glaucoma Analysis Using Level-set Image Processing
【24h】

ARGALI: An Automatic Cup-to-Disc Ratio Measurement System for Glaucoma Analysis Using Level-set Image Processing

机译:Argali:使用水平设定图像处理的青光眼分析的自动杯形比率测量系统

获取原文

摘要

Glaucoma is a leading cause of blindness worldwide, accounting for 12.3% of the permanently blind according to the World Heath Organization. The disease is particularly prevalent in Asia, with up to 50% of total glaucoma cases found in the region. Although glaucomatous damage is irreversible, studies have shown that early detection can be effective in slowing or halting glaucomatous atrophy. The ratio of the size of the optic cup to the optic disc, also known as the cup-to-disc ratio (CDR), is an important indicator for glaucoma assessment, since glaucomatous progression corresponds to increased excavation of the optic cup. In current clinical practice, the CDR is measured manually and can be subjective, limiting its use in screening for early detection. We describe the ARGALI system which automatically calculates the CDR from non-stereographic retinal fundus photographs, providing a fast, objective and consistent measurement. The ARGALI system consists of a series of steps. As the optic disc occupies only a small region of the entire retinal image, a region of interest is first extracted via pixel intensity analysis. Variational level-set algorithm is next used to segment the optic disc. Optic cup segmentation is more challenging due to the cup's interweavement with blood vessels and surrounding tissues. A multi-modal approach consisting of different methods is used extract the cup. To obtain a smoother contour, ellipse fitting is applied to the extracted cup and disc. A neural network has also been proposed to fuse the results obtained via the various modes. The ARGALI system was tested using images collected from patients at the Singapore Eye Research Institute and achieves an RMS error of 0.05 with a risk assessment accuracy of 95%. The results are promising for ARGALI to be developed into a low cost, objective and efficient screening system for automatic assessment glaucoma risk assessment.
机译:青光眼是全球失明的主要原因,根据世界荒地组织占永久盲目的12.3%。该疾病在亚洲尤为普遍,占该地区占青光眼案件的50%。虽然青光眼损伤是不可逆转的,但研究表明,早期检测可以有效地减缓或停止肺泡萎缩。光盘的尺寸与视光盘的比率,也称为杯盘比率(CDR)是青光眼评估的重要指标,因为胶水透进展对应于光学杯的挖掘增加。在目前的临床实践中,CDR手动测量,可以是主观的,限制其在筛选早期检测中的用途。我们描述了Argali系统,它自动计算了非立体视网膜眼底照片的CDR,提供了快速,客观和一致的测量。 Argali系统由一系列步骤组成。由于光盘仅占据整个视网膜图像的小区域,首先通过像素强度分析提取感兴趣区域。接下来使用变分级别集算法进行视镜盘。光学杯分割由于杯子与血管和周围组织的间之间的相互间平更具挑战性。使用由不同方法组成的多模态方法,提取杯子。为了获得更平滑的轮廓,椭圆拟合施加到提取的杯子和盘上。还提出了一种神经网络来熔化通过各种模式获得的结果。使用新加坡眼科研究所的患者收集的图像测试了argali系统,并实现了0.05的RMS误差,风险评估精度为95%。结果对Argali开发成低成本,客观和高效的筛选系统,用于自动评估青光眼风险评估。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号