利用人工智能技术估算血红蛋白

Suhas B. Dhoke, Anil R. Karwankar, V. Ratnaparkhe
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引用次数: 0

摘要

贫血是血红蛋白(Hb)含量低于正常值的一种情况。在这个项目中,血红蛋白值是使用ANN(人工神经网络)估计的。血液样本图像及其实际Hb值数据库是从当地实验室收集的。将图像样本的红、绿、蓝归一化值作为输入馈送到人工神经网络。基于从实验室获得的Hb计算值的氰铁血红蛋白方法作为输出。将人工神经网络模型输出结果与实际Hb值进行比较,计算网络的精度。本文比较了不同类型的神经网络在执行规定任务时的性能。可以观察到,图像中的红、绿、蓝三色成分与血液中的血红蛋白含量之间有很强的关系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Estimation of hemoglobin using AI technique
Anemia is a condition in which the hemoglobin (Hb) content becomes less than that of the normal value. In this project, hemoglobin value is estimated using ANN (Artificial Neural Network). Database of blood sample images and their actual Hb values is collected from a local laboratory. Red, green and blue normalized values of images' samples are fed to the ANN as input. Cyanemethemoglobin method based calculated values of Hb obtained from the laboratory are given as output. Comparing the outputs of ANN model results with actual Hb values, accuracy of the network is calculated. This paper covers comparison of performance of different types of Neural Networks for carrying out the stipulated task. It is observed that there is a strong relation between red, green and blue color components of the image with the hemoglobin content of the blood.
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