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IMPROVING HARD EXUDATE DETECTION IN RETINAL IMAGES THROUGH A COMBINATION OF LOCAL AND CONTEXTUAL INFORMATION

机译:通过局部和上下文信息的组合改善视网膜图像中的硬渗出物检测

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Contextual information is of paramount importance in medical image understanding to detect and differentiate pathologies, especially when interpreting difficult cases. Current computer-aided detection (CAD) systems typically employ only local information to classify candidates, without taking into account global image information or the relation of a candidate with neighboring structures. In this work, we improve the detection of hard exudates in retinal images incorporating contextual information in the CAD system. The context is described by means of high-level contextual-based features based on the spatial relation with surrounding anatomical landmarks and similar lesions. Results show that a contextual CAD system for hard exudate detection is superior to an approach that uses only local information, with a significant increase of the figure of merit of the Free Receiver Operating Characteristic (FROC) curve from 0.840 to 0.945.
机译:背景信息对于检测和区分病理学的理解至关重要,特别是在解释困难的情况下。 当前的计算机辅助检测(CAD)系统通常仅使用本地信息来对候选进行分类,而不考虑全局图像信息或候选与相邻结构的关系。 在这项工作中,我们改善了在包括CAD系统中的视网膜图像中的硬渗出物的检测。 基于与周围解剖学地标和类似病变的空间关系,通过基于高电平的基于环境的特征来描述上下文。 结果表明,用于硬渗出物检测的上下文CAD系统优于一种使用本地信息的方法,其自由接收器操作特性(FROC)曲线的优点的显着增加,从0.840到0.945。

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