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Computer Vision Algorithms for Retinal Image Analysis: Current Results and Future Directions

机译:视网膜图像分析的计算机视觉算法:当前的结果和未来方向

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Automated image analysis tools have the potential to play an important role in assisting in the diagnosis and treatment of retinal diseases.1 Problems that must be addressed in developing these tools include extraction of vascular and non-vascular features, segmentation of pathologies, unimodal and multimodal image registration, mosaic construction, and real-time systems. Research at Rensselaer Polytechnic Institute since the late 1990’s has focused on several of these problems. Most significantly, we have developed a series of registration and mosaic formation algorithms which have been validated on thousands of retinal images and have been extended beyond the retina application. While the core fundus image registration problem is essentially solved, important problems remain in many aspects of retinal image analysis.
机译:自动图像分析工具有可能在辅助视网膜疾病的诊断和治疗方面发挥重要作用。在开发这些工具时必须解决的问题包括提取血管和非血管特征,病理分割,单峰和多峰的分割图像配准,马赛克结构和实时系统。 1990年末以来君瑞工业研究所的研究专注于几个问题。最重要的是,我们开发了一系列注册和马赛克形成算法,这些算法已经验证了数千个视网膜图像,并且已经超出了视网膜应用。虽然核心眼底图像登记问题基本上解决了,但重要的问题仍然存在于视网膜图像分析的许多方面。

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