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Comparison of Red Blood Cells Counting using two Algorithms: Connected Component Labeling and Backprojection of Artificial Neural Network

机译:使用两种算法计数的红细胞比较:连接成分标签和人工神经网络的反调

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Accurate determination of the number of red blood cells (RBCs) is important, which leads to correct diagnosis to the patient. In this paper a comparison of counting procedure using two different algorithms is reported. They are the connected component labeling, based on morphological processing, and the back-projection of artificial neural network. The comparison is based on 23 images of blood samples taken from hematological microscopic system which is equipped with a Panasonic CCTV camera. Results are then benchmarked using a hematology analyzer Sysmex KX-21. Counting accuracies of 87,74 % and 86.97 % are obtained for the respective compared algorithms.
机译:准确测定红细胞数量(RBCS)是重要的,这导致对患者进行纠正诊断。本文报道了使用两种不同算法的计数过程的比较。它们是基于形态学处理的连接成分标记,以及人工神经网络的后投影。比较基于从配备有松下CCTV照相机的血液学显微镜系统中采取的23个血液样本图像。然后使用血液学分析仪Sysmex KX-21基准测试结果。为各种比较算法获得87,74%和86.97%的计数精度。

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