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首页> 外文会议>IEEE International Symposium on Biomedical Imaging: From Nano to Macro >Improving hard exudate detection in retinal images through a combination of local and contextual information
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Improving hard exudate detection in retinal images through a combination of local and contextual information

机译：通过结合本地信息和上下文信息来改善视网膜图像中的硬性渗出液检测

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摘要

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：在医学图像理解中，上下文信息对于检测和区分病变尤其是在解释困难病例时至关重要。当前的计算机辅助检测（CAD）系统通常仅使用本地信息对候选者进行分类，而不考虑全局图像信息或候选者与相邻结构的关系。在这项工作中，我们改进了在CAD系统中结合上下文信息的视网膜图像中硬质渗出液的检测。通过基于高级别基于上下文的特征来描述上下文，这些特征基于与周围解剖学界标和类似病变之间的空间关系。结果表明，用于硬性渗出物检测的上下文CAD系统优于仅使用本地信息的方法，自由接收器操作特征（FROC）曲线的优值从0.840显着提高到0.945。

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