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Extracting metadata from fundus images for the screening of diabetic retinopathy

机译:从眼底图像中提取元数据以筛选糖尿病视网膜病变

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In this paper we introduce a metadata schema for retinal disorders based on XML technology for successful grading. Besides the standard retinal anatomic components, the schema focuses on lesions generally caused by diabetic retinopathy. Suitable metadata classes are introduced to describe both the 2D and 3D appearance of the anatomic parts and the lesions, as well. The schema also contains schematrons to be able to derive more complex diagnosis based on the amount and spatial distribution of the lesions. The flexible design of the schema makes any further completions possible to cover acquisitions considering more fundus fields or lesions indicating other diseases. We also demonstrate the applicabilty of the schema by presenting some implementation details of it in a currently developed automatic screening system.
机译:在本文中,我们基于XML技术介绍了视网膜障碍的元数据模式,以成功分级。除了标准视网膜解剖组分之外,该模式侧重于糖尿病视网膜病变通常引起的病变。介绍合适的元数据类,以描述解剖部件和病变的2D和3D外观。该模式还包含模式,以便能够基于病变的数量和空间分布来导出更复杂的诊断。模式的灵活设计使得任何进一步的完成可以覆盖考虑更多眼底或病变指示其他疾病的病变。我们还通过在当前开发的自动筛选系统中展示它的一些实施细节来展示模式的应用。

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