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A neural network-based retinal imaging interface for optic disc localization in ophthalmic analyses

机译:用于眼科分析中视盘定位的基于神经网络的视网膜成像接口

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An automatic detection of the position of Optic Disc (OD) is a fundamental step in the analysis of human retina to examine the severity of some diseases or their pathologic progression. A precise localization of Optic Nerve and OD in retinal images reveals unavoidable, but the until now developed solutions providing a unique position seem to collapse when retinal images showing artefacts are analyzed. In previous works, the idea of evaluating multiple pixel determinations of the position of OD on captured fundus images by a multiple Processor has been adopted. In this work, a NN-based Positioning Interface, constituted by a Retinal Imaging System, a Neural Validity Classifier and a Positioning Processor for an accurate localization of the Reference point of OD, is developed. More in detail, the locations of multiple candidates are accurately validated by synthesizing a Neural Network behaving as a Classifier of Validity for regular/abnormal candidate reference points. Then, a Positioning Processor, which considers only validated midpoints, adopts the most suitable point as the Reference point of the OD for subsequent ophthalmic analyses. Simulation results are reported on selected fundus oculi images.
机译:视盘(OD)位置的自动检测是分析人类视网膜以检查某些疾病的严重程度或病理进展的基本步骤。视网膜图像中视神经和OD的精确定位是不可避免的,但是当分析显示伪影的视网膜图像时,迄今为止提供的独特位置的解决方案似乎已经崩溃。在以前的工作中,已经采用了通过多个处理器来评估获取的眼底图像上OD位置的多个像素确定的想法。在这项工作中,开发了由视网膜成像系统,神经有效性分类器和用于精确定位OD参考点的定位处理器组成的基于NN的定位接口。更详细地,通过合成作为常规/异常候选参考点的有效性分类器的神经网络,可以准确地验证多个候选的位置。然后,仅考虑经过验证的中点的定位处理器将最合适的点用作OD的参考点,以进行后续的眼科分析。在选定的眼底图像上报告了模拟结果。

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