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METHOD AND SYSTEM FOR DETERMINING TOTAL COUNT OF RED BLOOD CELLS IN PERIPHERAL BLOOD SMEAR

机译:确定外周血涂片中红色血液细胞总数的方法和系统

摘要

The present disclosure relates to a method and system for determining Total Count (TC) of RBCs in a Peripheral Blood Smear (PBS). The system receives a plurality of images from the monolayer of the PBS. Further, the system extracts, segments and identifies RBCs in each of the plurality of images using deep learning models. The system computes a value of each variable of a set of variables for each of the plurality of images. The set of variables includes foreground non-pallor area, density of RBCs, cell count, cell count ratio, foreground area and foreground hole-filled area. Furthermore, the system computes statistical parameters for each variable, over the plurality of images. The statistical parameters are provided as an input to supervised learning model, to determine TC of RBCs. Thus, the TC estimation system provides an efficient and robust method for estimating TC of RBCs using plurality of images of the PBS.
机译:本公开涉及一种用于确定外周血涂片(PBS)中的RBC的总计数(TC)的方法和系统。该系统从PBS的单层接收多个图像。此外,系统使用深度学习模型提取,分割和识别多个图像中的每个图像中的RBC。系统为多个图像中的每个图像计算一组变量中的每个变量的值。变量集包括前景非苍白面积,红细胞密度,细胞计数,细胞计数比率,前景面积和前景孔填充面积。此外,系统在多个图像上为每个变量计算统计参数。提供统计参数作为监督学习模型的输入,以确定RBC的TC。因此,TC估计系统提供了使用PBS的多个图像来估计RBC的TC的有效且鲁棒的方法。

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