首页> 外文会议>2017 IEEE 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and ManagementbElectronic resource >Determination of blood components (WBCs, RBCs, and Platelets) count in microscopic images using image processing and analysis
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Determination of blood components (WBCs, RBCs, and Platelets) count in microscopic images using image processing and analysis

机译:使用图像处理和分析确定显微图像中的血液成分(WBC,RBC和血小板)计数

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Blood is one of the most essential parts of the human body, and it comprises of the RBCs, WBCs, and Platelets. Complete blood count characterizes the condition of well-being. Hence, segmentation and identification of blood cells is very important. Up to this day, many hospitals and health centers still use the old conventional method which involves manual counting of blood cells. This technique is time-consuming and prone to erroneous outcomes. On the other hand, there are some costly machines like Hematology Analyzer, which health centers cannot afford. This paper presents a raspberry-pi based image analysis system that is designed to segment and count blood cells from microscopic images of blood using Hue, Saturation, and Value (HSV) thresholding method and connected component labeling, respectively. Detection and counting of RBCs, WBCs, and Platelets have been done on ten microscopic images. Statistical analysis was performed to compare the values measured by the proposed system to the actual complete blood count test result of each patient. It shows that the proposed system has a 90% and up accuracy with respect to the actual CBC tests result. In addition, an android application was also developed to aid the user, especially those who are in rural areas, in assessing the number of blood cells, and to send the results from GUI to a doctor or specialist through short message service (SMS) for remote diagnosis.
机译:血液是人体最重要的部分之一,由红细胞,白细胞和血小板组成。全血细胞计数是健康状况的特征。因此,血细胞的分割和识别非常重要。直到今天,许多医院和保健中心仍然使用旧的传统方法,该方法涉及手动计数血细胞。此技术非常耗时,并且容易产生错误的结果。另一方面,有一些昂贵的机器,例如血液分析仪,卫生中心买不起。本文介绍了一种基于树莓派的图像分析系统,该系统旨在分别使用色相,饱和度和值(HSV)阈值化方法和连接的组分标记对血液显微图像中的血细胞进行分段和计数。红细胞,白细胞和血小板的检测和计数已在十张显微图像上完成。进行统计分析,以将建议的系统测量的值与每个患者的实际全血细胞计数测试结果进行比较。结果表明,相对于实际的CBC测试结果,所提出的系统具有90%的精度。此外,还开发了一个android应用程序,以帮助用户(尤其是农村地区的用户)评估血细胞数量,并通过短信服务(SMS)将GUI的结果发送给医生或专科医生,以进行以下操作:远程诊断。

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