Computer analysis of optic disc images in glaucoma

描述（由申请人提供）：青光眼的诊断、治疗和研究依赖于对视盘（或视神经乳头）、视野和眼内压的复杂判断。目前的视盘评价标准要求观察者对视盘的立体照片进行定性判断，这是一种不太理想的方法。尽管进行了大量研究，但还没有任何方法能够最终改善这种传统方法：当代视盘分析仪通常使用仪器特定的图像捕获方法，并对视盘的各种解剖特征进行定量估计。我们的目标是通过将计算机工程中的先进图像分析方法应用于青光眼的基本诊断问题-检测随时间推移的视盘图像的变化或稳定性来改进视盘诊断方法。在宾夕法尼亚大学的专业知识，在临床青光眼，转化研究（R。Stone，PI; E.米勒，J. Piltz-Seymour等人）和生物统计学（M. Maguire，G. S.英）与Sarnoff公司（B. Hanna，H. Sawhney等）在生物工程研究伙伴关系中具有四个具体目标：1）开发和验证用于自动对准视盘图像的鲁棒配准算法; 2）开发自动多视图分析方法以从视盘立体图像提取相对局部变化参数; 3）开发交互式工具，以帮助观察者对视盘图像进行分级，并帮助临床解释自动变化检测和立体算法;以及4）进行视盘变化检测工具的初始验证研究。我们的立体计划主要不同于其他视神经分析方法，但它为验证、临床护理和研究提供了许多现代眼底分析仪特定仪器格式无法实现的优势。只需要一台个人电脑和软件来分析视盘图像，我们的方法是临床直观的，可以适应软件和相机技术的改进，与许多图像格式兼容，允许使用存档眼底照片，是具有成本效益的。立体恢复的改进方法将允许强大的检测视盘的稳定性或变化，它提供了很大的希望，为推进青光眼的视神经诊断。

DESCRIPTION (provided by applicant): Glaucoma diagnosis, management and research depend on complex judgments of the optic disc (or optic nerve head), visual field and intraocular pressure. The current standard of optic disc evaluation requires qualitative observer judgments of stereoscopic photographs of the optic disc, a less than optimal method. Despite much research, no methods have yet conclusively improved over this conventional Approach: Contemporary optic disc analyzers typically use instrument-specific image capture methods and derive quantitative estimates for various anatomical features of the optic disc. Our goal is to improve the methods of optic disc diagnosis by applying advanced image analysis methods from computer engineering to the essential diagnostic problem in glaucoma - detecting change or stability in optic disc images over time. Expertise at the University of Pennsylvania in clinical glaucoma, translational research (R. Stone, PI; E. Miller, J. Piltz-Seymour and others) and biostatistics (M. Maguire, G.-S. Ying) is merged with engineering expertise in computer image analysis at Sarnoff Corporation (B. Hanna, H. Sawhney, and others) in a Bioengineering Research Partnership with four Specific Aims: 1) Develop and validate robust registration algorithms for automatic alignment of optic disc images; 2) Develop an automated multiple-view analysis approach to extract relative, local change parameters from optic disc stereo images; 3) Develop interactive tools to assist in observer grading of optic disc images and in clinical interpretation of the automated change detection and stereoscopic algorithms; and 4) Conduct initial validation studies of the optic disc change detection tools. Our plan to address stereo primarily differs from other approaches to optic nerve analysis, but it offers many advantages for validation, clinical care and research not possible with the instrument-specific formats of contemporary fundus analyzers. Requiring only a personal computer and software to analyze optic disc images, our approach is clinically intuitive, can accommodate improvements in software and camera technology, is compatible with many image formats, permits use of archived fundus photos and is cost-effective. The refined approach to stereo recovery will permit robust detection of optic disc stability or change, and it offers great promise for advancing optic nerve diagnosis in glaucoma.