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首页> 外文会议>Mediterranean Conference on Medical and Biological Engineering and Computing >Learning Optimal Matched Filters for Retinal Vessel Segmentation with ADA-Boost
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Learning Optimal Matched Filters for Retinal Vessel Segmentation with ADA-Boost

机译：使用ADA-Boost学习用于视网膜血管分割的最佳匹配过滤器

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摘要

Retinopathy of Prematurity (ROP) is an eye disease that affects premature infants. Its signs are tortuosity and dilation of retinal vessels, which are subjectively evaluated by clinicians for the diagnosis and the follow-up of the disease. The availability of algorithms for vascular segmentation would allow vessel geometrical characterization, and hence the quantitative and objective clinical evaluation of the these signs. Unfortunately, algorithms designed for adults' fundus images do not work well in infants' fundus images, due to their very low quality. At variance with available methods, we propose a data-driven approach, in which the system learns an array of optimal discriminative convolution kernels, to be employed in a ADA-boost supervised classification. The array is employed as a rotating bank of matched filters, whose response is used by the boosted linear classifier to provide a classification of each image pixel into the two classes of interest (vessel/background). In order to test the generality of the approach, we assessed the performance of the proposed method both on adults' fundus images using the DRIVE dataset, and also on infants' images by cross-validation on a dataset of 20 images acquired with a RetCam fundus camera. Average accuracy and Matthews' correlation coefficient are respectively 0.94 and 0.69 for DRIVE and 0.98 and 0.66 for the Retcam dataset with respect to the manual ground truth references.
机译：早产儿（ROP）的视网膜病变是影响早产儿的眼病。其迹象是视网膜血管的曲纹和扩张，这些血管是由临床医生进行的主观评估，用于诊断和疾病的随访。用于血管分割的算法的可用性将允许血管几何表征，从而占据这些标志的定量和客观临床评价。遗憾的是，由于其质量很低，为成年人的眼底图像设计的算法在婴儿的眼底图像上不起作用。在具有可用方法的方差，我们提出了一种数据驱动方法，其中系统学习了一系列最佳鉴别卷积内核，以便在ADA-Boost监督分类中使用。该阵列用作匹配滤波器的旋转组，其响应由升压的线性分类器使用，以提供每个图像像素的分类到两个感兴趣的兴趣（血管/背景）中。为了测试该方法的一般性，我们通过在用Retcam USPES获取的20个图像的数据集上通过交叉验证来评估成人的眼底图像上提出的方法的性能。相机。对于手动地面真理参考，平均精度和马修的相关系数分别为0.94和0.69的驱动和0.98和0.66。

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