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Cell classification for diagnostic of reactive histocytic hyperplasia using neural networks

机译:使用神经网络诊断反应性组织细胞增生的细胞分类

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The most important step in the medical treatment of patients is getting the correct diagnosis. Diagnostic procedure is based upon many facts gathered through the process of various examinations. Important information can be gathered by visual examination of tissue samples using a microscope. This paper presents one method for automatic analysis of microscopic bone marrow images in order to help physicians in the diagnosis of reactive histiocytosis. Morphological parameters of bone marrow cells are measured by the means of digital image processing and after that measured parameters are analyzed using a neural network to produce helpful diagnostic informations. By just a visual examination a physician can only estimate cell parameters, so the diagnostic procedure is mostly based on his experience. Using the described automatic system, relevant parameters can be precisely measured and a neural network is used to accumulate and keep the physician's experience and knowledge so that correct conclusions can be made.
机译:对患者进行医学治疗的最重要步骤是获得正确的诊断。诊断程序基于通过各种检查过程收集到的许多事实。重要信息可以通过使用显微镜目视检查组织样本来收集。本文提出了一种自动分析显微骨髓图像的方法,以帮助医生诊断反应性组织细胞增生症。通过数字图像处理测量骨髓细胞的形态学参数,然后使用神经网络分析测量的参数以产生有用的诊断信息。仅仅通过目视检查,医生就只能估计细胞参数,因此诊断过程主要基于他的经验。使用所描述的自动系统,可以精确地测量相关参数,并使用神经网络来累积并保持医师的经验和知识,以便可以得出正确的结论。

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