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Red Blood based disease screening using marker controlled watershed segmentation and post-processing

机译:使用标记控制流域分割和后处理的红血基疾病筛选

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Cell segmentation is a challenging problem due to the complexity and nature of the blood cells. Traditional methods of counting the cells are slow, error prone and often influenced by the performance of the operator. This paper aims to segment and count Red Blood Cells (RBCs) automatically shown in microscopic blood images to determine the condition of the person under examination. We also aim to increase the accuracy of segmentation by precisely looking into the counting of the overlapped cells which is the most conventional challenging task faced by many researchers. The RBCs in this paper are segmented using the integration of marker controlled watershed segmentation with morphological operations. The result of the proposed algorithm was validated with the manual counting method, and a good conformity of about 93.13 % was obtained. The future work will involve segmentation of more complex overlapping cells and the development of Smartphone based realtime disease screening system.
机译:由于血细胞的复杂性和性质,细胞分割是一个具有挑战性的问题。 传统的计数细胞的方法缓慢,易于误差,并且经常受到操作员性能的影响。 本文旨在将红细胞(RBC)自动显示在微观血液图像中,以确定检验中的人的状况。 我们旨在通过精确地研究重叠的细胞的计数,提高分割的准确性,这是许多研究人员面临的最常规具有挑战性的任务。 本文中的RBCS使用与形态操作的标记控制流域分段集成进行分段。 用手动计数方法验证了所提出的算法的结果,获得了约93.13%的良好符合性。 未来的工作将涉及分割更复杂的重叠细胞以及基于智能手机的实时疾病筛选系统的开发。

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